diff --git a/datafusion-examples/examples/dataframe_subquery.rs b/datafusion-examples/examples/dataframe_subquery.rs
index e798751b3353..f3cdd048968b 100644
--- a/datafusion-examples/examples/dataframe_subquery.rs
+++ b/datafusion-examples/examples/dataframe_subquery.rs
@@ -15,7 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use arrow_schema::DataType;
+use datafusion_common::logical_type::LogicalType;
 use std::sync::Arc;
 
 use datafusion::error::Result;
@@ -48,7 +48,7 @@ async fn where_scalar_subquery(ctx: &SessionContext) -> Result<()> {
             scalar_subquery(Arc::new(
                 ctx.table("t2")
                     .await?
-                    .filter(out_ref_col(DataType::Utf8, "t1.c1").eq(col("t2.c1")))?
+                    .filter(out_ref_col(LogicalType::Utf8, "t1.c1").eq(col("t2.c1")))?
                     .aggregate(vec![], vec![avg(col("t2.c2"))])?
                     .select(vec![avg(col("t2.c2"))])?
                     .into_unoptimized_plan(),
@@ -91,7 +91,7 @@ async fn where_exist_subquery(ctx: &SessionContext) -> Result<()> {
         .filter(exists(Arc::new(
             ctx.table("t2")
                 .await?
-                .filter(out_ref_col(DataType::Utf8, "t1.c1").eq(col("t2.c1")))?
+                .filter(out_ref_col(LogicalType::Utf8, "t1.c1").eq(col("t2.c1")))?
                 .select(vec![col("t2.c2")])?
                 .into_unoptimized_plan(),
         )))?
diff --git a/datafusion-examples/examples/expr_api.rs b/datafusion-examples/examples/expr_api.rs
index 591f6ac3de95..e2b54fb68daf 100644
--- a/datafusion-examples/examples/expr_api.rs
+++ b/datafusion-examples/examples/expr_api.rs
@@ -28,6 +28,9 @@ use datafusion::functions_aggregate::first_last::first_value_udaf;
 use datafusion::optimizer::simplify_expressions::ExprSimplifier;
 use datafusion::physical_expr::{analyze, AnalysisContext, ExprBoundaries};
 use datafusion::prelude::*;
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::schema::LogicalSchema;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_common::{ScalarValue, ToDFSchema};
 use datafusion_expr::execution_props::ExecutionProps;
 use datafusion_expr::expr::BinaryExpr;
@@ -156,7 +159,7 @@ fn simplify_demo() -> Result<()> {
     // However, DataFusion's simplification logic can do this for you
 
     // you need to tell DataFusion the type of column "ts":
-    let schema = Schema::new(vec![make_ts_field("ts")]).to_dfschema_ref()?;
+    let schema = LogicalSchema::from(Schema::new(vec![make_ts_field("ts")])).to_dfschema_ref()?;
 
     // And then build a simplifier
     // the ExecutionProps carries information needed to simplify
@@ -177,10 +180,10 @@ fn simplify_demo() -> Result<()> {
     );
 
     // here are some other examples of what DataFusion is capable of
-    let schema = Schema::new(vec![
+    let schema = LogicalSchema::from(Schema::new(vec![
         make_field("i", DataType::Int64),
         make_field("b", DataType::Boolean),
-    ])
+    ]))
     .to_dfschema_ref()?;
     let context = SimplifyContext::new(&props).with_schema(schema.clone());
     let simplifier = ExprSimplifier::new(context);
@@ -211,7 +214,7 @@ fn simplify_demo() -> Result<()> {
     // String --> Date simplification
     // `cast('2020-09-01' as date)` --> 18500
     assert_eq!(
-        simplifier.simplify(lit("2020-09-01").cast_to(&DataType::Date32, &schema)?)?,
+        simplifier.simplify(lit("2020-09-01").cast_to(&LogicalType::Date32, &schema)?)?,
         lit(ScalarValue::Date32(Some(18506)))
     );
 
@@ -258,7 +261,7 @@ fn range_analysis_demo() -> Result<()> {
     let analysis_result = analyze(
         &physical_expr,
         AnalysisContext::new(boundaries),
-        df_schema.as_ref(),
+        &df_schema.into(),
     )?;
 
     // The results of the analysis is an range, encoded as an `Interval`,  for
@@ -293,14 +296,14 @@ fn expression_type_demo() -> Result<()> {
     // a schema. In this case we create a schema where the column `c` is of
     // type Utf8 (a String / VARCHAR)
     let schema = DFSchema::from_unqualifed_fields(
-        vec![Field::new("c", DataType::Utf8, true)].into(),
+        vec![LogicalField::new("c", LogicalType::Utf8, true)].into(),
         HashMap::new(),
     )?;
     assert_eq!("Utf8", format!("{}", expr.get_type(&schema).unwrap()));
 
     // Using a schema where the column `foo` is of type Int32
     let schema = DFSchema::from_unqualifed_fields(
-        vec![Field::new("c", DataType::Int32, true)].into(),
+        vec![LogicalField::new("c", LogicalType::Int32, true)].into(),
         HashMap::new(),
     )?;
     assert_eq!("Int32", format!("{}", expr.get_type(&schema).unwrap()));
@@ -310,8 +313,8 @@ fn expression_type_demo() -> Result<()> {
     let expr = col("c1") + col("c2");
     let schema = DFSchema::from_unqualifed_fields(
         vec![
-            Field::new("c1", DataType::Int32, true),
-            Field::new("c2", DataType::Float32, true),
+            LogicalField::new("c1", LogicalType::Int32, true),
+            LogicalField::new("c2", LogicalType::Float32, true),
         ]
         .into(),
         HashMap::new(),
diff --git a/datafusion-examples/examples/function_factory.rs b/datafusion-examples/examples/function_factory.rs
index f57b3bf60404..bf2a44e7063e 100644
--- a/datafusion-examples/examples/function_factory.rs
+++ b/datafusion-examples/examples/function_factory.rs
@@ -22,6 +22,7 @@ use datafusion::error::Result;
 use datafusion::execution::context::{
     FunctionFactory, RegisterFunction, SessionContext, SessionState,
 };
+use datafusion_common::logical_type::extension::ExtensionType;
 use datafusion_common::tree_node::{Transformed, TreeNode};
 use datafusion_common::{exec_err, internal_err, DataFusionError};
 use datafusion_expr::simplify::{ExprSimplifyResult, SimplifyInfo};
@@ -216,13 +217,14 @@ impl TryFrom<CreateFunction> for ScalarFunctionWrapper {
                 .expect("Expression has to be defined!"),
             return_type: definition
                 .return_type
-                .expect("Return type has to be defined!"),
+                .expect("Return type has to be defined!")
+                .physical_type(),
             signature: Signature::exact(
                 definition
                     .args
                     .unwrap_or_default()
                     .into_iter()
-                    .map(|a| a.data_type)
+                    .map(|a| a.data_type.physical_type())
                     .collect(),
                 definition
                     .params
diff --git a/datafusion-examples/examples/rewrite_expr.rs b/datafusion-examples/examples/rewrite_expr.rs
index 06286d5d66ed..ed748288ff3d 100644
--- a/datafusion-examples/examples/rewrite_expr.rs
+++ b/datafusion-examples/examples/rewrite_expr.rs
@@ -17,6 +17,7 @@
 
 use arrow::datatypes::{DataType, Field, Schema, SchemaRef};
 use datafusion_common::config::ConfigOptions;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_common::tree_node::{Transformed, TransformedResult, TreeNode};
 use datafusion_common::{plan_err, DataFusionError, Result, ScalarValue};
 use datafusion_expr::{
@@ -211,7 +212,7 @@ impl ContextProvider for MyContextProvider {
         None
     }
 
-    fn get_variable_type(&self, _variable_names: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, _variable_names: &[String]) -> Option<LogicalType> {
         None
     }
 
diff --git a/datafusion/common/src/column.rs b/datafusion/common/src/column.rs
index e36a4f890644..ac54e87fd617 100644
--- a/datafusion/common/src/column.rs
+++ b/datafusion/common/src/column.rs
@@ -17,8 +17,6 @@
 
 //! Column
 
-use arrow_schema::{Field, FieldRef};
-
 use crate::error::_schema_err;
 use crate::utils::{parse_identifiers_normalized, quote_identifier};
 use crate::{DFSchema, DataFusionError, Result, SchemaError, TableReference};
@@ -27,6 +25,7 @@ use std::convert::Infallible;
 use std::fmt;
 use std::str::FromStr;
 use std::sync::Arc;
+use crate::logical_type::field::{LogicalField, LogicalFieldRef};
 
 /// A named reference to a qualified field in a schema.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
@@ -349,15 +348,15 @@ impl From<String> for Column {
 }
 
 /// Create a column, use qualifier and field name
-impl From<(Option<&TableReference>, &Field)> for Column {
-    fn from((relation, field): (Option<&TableReference>, &Field)) -> Self {
+impl From<(Option<&TableReference>, &LogicalField)> for Column {
+    fn from((relation, field): (Option<&TableReference>, &LogicalField)) -> Self {
         Self::new(relation.cloned(), field.name())
     }
 }
 
 /// Create a column, use qualifier and field name
-impl From<(Option<&TableReference>, &FieldRef)> for Column {
-    fn from((relation, field): (Option<&TableReference>, &FieldRef)) -> Self {
+impl From<(Option<&TableReference>, &LogicalFieldRef)> for Column {
+    fn from((relation, field): (Option<&TableReference>, &LogicalFieldRef)) -> Self {
         Self::new(relation.cloned(), field.name())
     }
 }
@@ -380,7 +379,7 @@ impl fmt::Display for Column {
 mod tests {
     use super::*;
     use arrow::datatypes::DataType;
-    use arrow_schema::SchemaBuilder;
+    use arrow_schema::{Field, SchemaBuilder};
 
     fn create_qualified_schema(qualifier: &str, names: Vec<&str>) -> Result<DFSchema> {
         let mut schema_builder = SchemaBuilder::new();
@@ -389,7 +388,7 @@ mod tests {
                 .iter()
                 .map(|f| Field::new(*f, DataType::Boolean, true)),
         );
-        let schema = Arc::new(schema_builder.finish());
+        let schema = Arc::new(schema_builder.finish().into());
         DFSchema::try_from_qualified_schema(qualifier, &schema)
     }
 
diff --git a/datafusion/common/src/dfschema.rs b/datafusion/common/src/dfschema.rs
index 0dab13d08731..f407383319ac 100644
--- a/datafusion/common/src/dfschema.rs
+++ b/datafusion/common/src/dfschema.rs
@@ -30,8 +30,12 @@ use crate::{
 };
 
 use arrow::compute::can_cast_types;
-use arrow::datatypes::{DataType, Field, FieldRef, Fields, Schema, SchemaRef};
-use arrow_schema::SchemaBuilder;
+use arrow::datatypes::{DataType, Field, Fields, Schema, SchemaRef};
+use crate::logical_type::extension::ExtensionType;
+use crate::logical_type::field::{LogicalField, LogicalFieldRef};
+use crate::logical_type::fields::LogicalFields;
+use crate::logical_type::LogicalType;
+use crate::logical_type::schema::{LogicalSchema, LogicalSchemaBuilder, LogicalSchemaRef};
 
 /// A reference-counted reference to a [DFSchema].
 pub type DFSchemaRef = Arc<DFSchema>;
@@ -62,7 +66,7 @@ pub type DFSchemaRef = Arc<DFSchema>;
 ///    Field::new("c1", DataType::Int32, false),
 /// ]);
 ///
-/// let df_schema = DFSchema::try_from_qualified_schema("t1", &arrow_schema).unwrap();
+/// let df_schema = DFSchema::try_from_qualified_schema("t1", &arrow_schema.into()).unwrap();
 /// let column = Column::from_qualified_name("t1.c1");
 /// assert!(df_schema.has_column(&column));
 ///
@@ -107,9 +111,9 @@ pub type DFSchemaRef = Arc<DFSchema>;
 #[derive(Debug, Clone, PartialEq, Eq)]
 pub struct DFSchema {
     /// Inner Arrow schema reference.
-    inner: SchemaRef,
+    inner: LogicalSchemaRef,
     /// Optional qualifiers for each column in this schema. In the same order as
-    /// the `self.inner.fields()`
+    /// the `self.inner.fields`
     field_qualifiers: Vec<Option<TableReference>>,
     /// Stores functional dependencies in the schema.
     functional_dependencies: FunctionalDependencies,
@@ -119,7 +123,7 @@ impl DFSchema {
     /// Creates an empty `DFSchema`
     pub fn empty() -> Self {
         Self {
-            inner: Arc::new(Schema::new([])),
+            inner: Arc::new(LogicalSchema::new([])),
             field_qualifiers: vec![],
             functional_dependencies: FunctionalDependencies::empty(),
         }
@@ -128,26 +132,26 @@ impl DFSchema {
     /// Return a reference to the inner Arrow [`Schema`]
     ///
     /// Note this does not have the qualifier information
-    pub fn as_arrow(&self) -> &Schema {
+    pub fn as_arrow(&self) -> &LogicalSchema {
         self.inner.as_ref()
     }
 
     /// Return a reference to the inner Arrow [`SchemaRef`]
     ///
     /// Note this does not have the qualifier information
-    pub fn inner(&self) -> &SchemaRef {
+    pub fn inner(&self) -> &LogicalSchemaRef {
         &self.inner
     }
 
     /// Create a `DFSchema` from an Arrow schema where all the fields have a given qualifier
     pub fn new_with_metadata(
-        qualified_fields: Vec<(Option<TableReference>, Arc<Field>)>,
+        qualified_fields: Vec<(Option<TableReference>, Arc<LogicalField>)>,
         metadata: HashMap<String, String>,
     ) -> Result<Self> {
-        let (qualifiers, fields): (Vec<Option<TableReference>>, Vec<Arc<Field>>) =
+        let (qualifiers, fields): (Vec<Option<TableReference>>, Vec<Arc<LogicalField>>) =
             qualified_fields.into_iter().unzip();
 
-        let schema = Arc::new(Schema::new_with_metadata(fields, metadata));
+        let schema = Arc::new(LogicalSchema::new_with_metadata(fields, metadata));
 
         let dfschema = Self {
             inner: schema,
@@ -160,11 +164,11 @@ impl DFSchema {
 
     /// Create a new `DFSchema` from a list of Arrow [Field]s
     pub fn from_unqualifed_fields(
-        fields: Fields,
+        fields: LogicalFields,
         metadata: HashMap<String, String>,
     ) -> Result<Self> {
         let field_count = fields.len();
-        let schema = Arc::new(Schema::new_with_metadata(fields, metadata));
+        let schema = Arc::new(LogicalSchema::new_with_metadata(fields, metadata));
         let dfschema = Self {
             inner: schema,
             field_qualifiers: vec![None; field_count],
@@ -180,7 +184,7 @@ impl DFSchema {
     /// `DFSchema::try_from`.
     pub fn try_from_qualified_schema(
         qualifier: impl Into<TableReference>,
-        schema: &Schema,
+        schema: &LogicalSchema,
     ) -> Result<Self> {
         let qualifier = qualifier.into();
         let schema = DFSchema {
@@ -195,7 +199,7 @@ impl DFSchema {
     /// Create a `DFSchema` from an Arrow schema where all the fields have a given qualifier
     pub fn from_field_specific_qualified_schema(
         qualifiers: Vec<Option<TableReference>>,
-        schema: &SchemaRef,
+        schema: &LogicalSchemaRef,
     ) -> Result<Self> {
         let dfschema = Self {
             inner: schema.clone(),
@@ -211,7 +215,7 @@ impl DFSchema {
         let mut qualified_names = BTreeSet::new();
         let mut unqualified_names = BTreeSet::new();
 
-        for (field, qualifier) in self.inner.fields().iter().zip(&self.field_qualifiers) {
+        for (field, qualifier) in self.inner.fields.iter().zip(&self.field_qualifiers) {
             if let Some(qualifier) = qualifier {
                 qualified_names.insert((qualifier, field.name()));
             } else if !unqualified_names.insert(field.name()) {
@@ -250,8 +254,8 @@ impl DFSchema {
     /// Create a new schema that contains the fields from this schema followed by the fields
     /// from the supplied schema. An error will be returned if there are duplicate field names.
     pub fn join(&self, schema: &DFSchema) -> Result<Self> {
-        let mut schema_builder = SchemaBuilder::new();
-        schema_builder.extend(self.inner.fields().iter().cloned());
+        let mut schema_builder = LogicalSchemaBuilder::new();
+        schema_builder.extend(self.inner.fields.iter().cloned());
         schema_builder.extend(schema.fields().iter().cloned());
         let new_schema = schema_builder.finish();
 
@@ -278,23 +282,23 @@ impl DFSchema {
             return;
         }
 
-        let self_fields: HashSet<(Option<&TableReference>, &FieldRef)> =
+        let self_fields: HashSet<(Option<&TableReference>, &LogicalFieldRef)> =
             self.iter().collect();
         let self_unqualified_names: HashSet<&str> = self
             .inner
             .fields
             .iter()
-            .map(|field| field.name().as_str())
+            .map(|field| field.name())
             .collect();
 
-        let mut schema_builder = SchemaBuilder::from(self.inner.fields.clone());
+        let mut schema_builder = LogicalSchemaBuilder::from(self.inner.fields.clone());
         let mut qualifiers = Vec::new();
         for (qualifier, field) in other_schema.iter() {
             // skip duplicate columns
             let duplicated_field = match qualifier {
                 Some(q) => self_fields.contains(&(Some(q), field)),
                 // for unqualified columns, check as unqualified name
-                None => self_unqualified_names.contains(field.name().as_str()),
+                None => self_unqualified_names.contains(field.name()),
             };
             if !duplicated_field {
                 // self.inner.fields.push(field.clone());
@@ -312,19 +316,19 @@ impl DFSchema {
     }
 
     /// Get a list of fields
-    pub fn fields(&self) -> &Fields {
+    pub fn fields(&self) -> &LogicalFields {
         &self.inner.fields
     }
 
     /// Returns an immutable reference of a specific `Field` instance selected using an
     /// offset within the internal `fields` vector
-    pub fn field(&self, i: usize) -> &Field {
+    pub fn field(&self, i: usize) -> &LogicalField {
         &self.inner.fields[i]
     }
 
     /// Returns an immutable reference of a specific `Field` instance selected using an
     /// offset within the internal `fields` vector and its qualifier
-    pub fn qualified_field(&self, i: usize) -> (Option<&TableReference>, &Field) {
+    pub fn qualified_field(&self, i: usize) -> (Option<&TableReference>, &LogicalField) {
         (self.field_qualifiers[i].as_ref(), self.field(i))
     }
 
@@ -391,7 +395,7 @@ impl DFSchema {
         &self,
         qualifier: Option<&TableReference>,
         name: &str,
-    ) -> Result<&Field> {
+    ) -> Result<&LogicalField> {
         if let Some(qualifier) = qualifier {
             self.field_with_qualified_name(qualifier, name)
         } else {
@@ -404,7 +408,7 @@ impl DFSchema {
         &self,
         qualifier: Option<&TableReference>,
         name: &str,
-    ) -> Result<(Option<&TableReference>, &Field)> {
+    ) -> Result<(Option<&TableReference>, &LogicalField)> {
         if let Some(qualifier) = qualifier {
             let idx = self
                 .index_of_column_by_name(Some(qualifier), name)
@@ -416,7 +420,7 @@ impl DFSchema {
     }
 
     /// Find all fields having the given qualifier
-    pub fn fields_with_qualified(&self, qualifier: &TableReference) -> Vec<&Field> {
+    pub fn fields_with_qualified(&self, qualifier: &TableReference) -> Vec<&LogicalField> {
         self.iter()
             .filter(|(q, _)| q.map(|q| q.eq(qualifier)).unwrap_or(false))
             .map(|(_, f)| f.as_ref())
@@ -435,7 +439,7 @@ impl DFSchema {
     }
 
     /// Find all fields that match the given name
-    pub fn fields_with_unqualified_name(&self, name: &str) -> Vec<&Field> {
+    pub fn fields_with_unqualified_name(&self, name: &str) -> Vec<&LogicalField> {
         self.fields()
             .iter()
             .filter(|field| field.name() == name)
@@ -447,7 +451,7 @@ impl DFSchema {
     pub fn qualified_fields_with_unqualified_name(
         &self,
         name: &str,
-    ) -> Vec<(Option<&TableReference>, &Field)> {
+    ) -> Vec<(Option<&TableReference>, &LogicalField)> {
         self.iter()
             .filter(|(_, field)| field.name() == name)
             .map(|(qualifier, field)| (qualifier, field.as_ref()))
@@ -466,7 +470,7 @@ impl DFSchema {
     pub fn columns(&self) -> Vec<Column> {
         self.iter()
             .map(|(qualifier, field)| {
-                Column::new(qualifier.cloned(), field.name().clone())
+                Column::new(qualifier.cloned(), field.name())
             })
             .collect()
     }
@@ -475,7 +479,7 @@ impl DFSchema {
     pub fn qualified_field_with_unqualified_name(
         &self,
         name: &str,
-    ) -> Result<(Option<&TableReference>, &Field)> {
+    ) -> Result<(Option<&TableReference>, &LogicalField)> {
         let matches = self.qualified_fields_with_unqualified_name(name);
         match matches.len() {
             0 => Err(unqualified_field_not_found(name, self)),
@@ -507,7 +511,7 @@ impl DFSchema {
     }
 
     /// Find the field with the given name
-    pub fn field_with_unqualified_name(&self, name: &str) -> Result<&Field> {
+    pub fn field_with_unqualified_name(&self, name: &str) -> Result<&LogicalField> {
         let matches = self.qualified_fields_with_unqualified_name(name);
         match matches.len() {
             0 => Err(unqualified_field_not_found(name, self)),
@@ -543,7 +547,7 @@ impl DFSchema {
         &self,
         qualifier: &TableReference,
         name: &str,
-    ) -> Result<&Field> {
+    ) -> Result<&LogicalField> {
         let idx = self
             .index_of_column_by_name(Some(qualifier), name)
             .ok_or_else(|| field_not_found(Some(qualifier.clone()), name, self))?;
@@ -552,7 +556,7 @@ impl DFSchema {
     }
 
     /// Find the field with the given qualified column
-    pub fn field_from_column(&self, column: &Column) -> Result<&Field> {
+    pub fn field_from_column(&self, column: &Column) -> Result<&LogicalField> {
         match &column.relation {
             Some(r) => self.field_with_qualified_name(r, &column.name),
             None => self.field_with_unqualified_name(&column.name),
@@ -563,7 +567,7 @@ impl DFSchema {
     pub fn qualified_field_from_column(
         &self,
         column: &Column,
-    ) -> Result<(Option<&TableReference>, &Field)> {
+    ) -> Result<(Option<&TableReference>, &LogicalField)> {
         self.qualified_field_with_name(column.relation.as_ref(), &column.name)
     }
 
@@ -658,7 +662,7 @@ impl DFSchema {
         self_fields.zip(other_fields).all(|((q1, f1), (q2, f2))| {
             q1 == q2
                 && f1.name() == f2.name()
-                && Self::datatype_is_semantically_equal(f1.data_type(), f2.data_type())
+                && Self::datatype_is_semantically_equal(&f1.data_type().physical_type(), &f2.data_type().physical_type())
         })
     }
 
@@ -666,40 +670,8 @@ impl DFSchema {
     /// than datatype_is_semantically_equal in that a Dictionary<K,V> type is logically
     /// equal to a plain V type, but not semantically equal. Dictionary<K1, V1> is also
     /// logically equal to Dictionary<K2, V1>.
-    pub fn datatype_is_logically_equal(dt1: &DataType, dt2: &DataType) -> bool {
-        // check nested fields
-        match (dt1, dt2) {
-            (DataType::Dictionary(_, v1), DataType::Dictionary(_, v2)) => {
-                v1.as_ref() == v2.as_ref()
-            }
-            (DataType::Dictionary(_, v1), othertype) => v1.as_ref() == othertype,
-            (othertype, DataType::Dictionary(_, v1)) => v1.as_ref() == othertype,
-            (DataType::List(f1), DataType::List(f2))
-            | (DataType::LargeList(f1), DataType::LargeList(f2))
-            | (DataType::FixedSizeList(f1, _), DataType::FixedSizeList(f2, _))
-            | (DataType::Map(f1, _), DataType::Map(f2, _)) => {
-                Self::field_is_logically_equal(f1, f2)
-            }
-            (DataType::Struct(fields1), DataType::Struct(fields2)) => {
-                let iter1 = fields1.iter();
-                let iter2 = fields2.iter();
-                fields1.len() == fields2.len() &&
-                        // all fields have to be the same
-                    iter1
-                    .zip(iter2)
-                        .all(|(f1, f2)| Self::field_is_logically_equal(f1, f2))
-            }
-            (DataType::Union(fields1, _), DataType::Union(fields2, _)) => {
-                let iter1 = fields1.iter();
-                let iter2 = fields2.iter();
-                fields1.len() == fields2.len() &&
-                    // all fields have to be the same
-                    iter1
-                        .zip(iter2)
-                        .all(|((t1, f1), (t2, f2))| t1 == t2 && Self::field_is_logically_equal(f1, f2))
-            }
-            _ => dt1 == dt2,
-        }
+    pub fn datatype_is_logically_equal(dt1: &LogicalType, dt2: &LogicalType) -> bool {
+        dt1 == dt2
     }
 
     /// Returns true of two [`DataType`]s are semantically equal (same
@@ -749,11 +721,6 @@ impl DFSchema {
         }
     }
 
-    fn field_is_logically_equal(f1: &Field, f2: &Field) -> bool {
-        f1.name() == f2.name()
-            && Self::datatype_is_logically_equal(f1.data_type(), f2.data_type())
-    }
-
     fn field_is_semantically_equal(f1: &Field, f2: &Field) -> bool {
         f1.name() == f2.name()
             && Self::datatype_is_semantically_equal(f1.data_type(), f2.data_type())
@@ -796,10 +763,10 @@ impl DFSchema {
     }
 
     /// Iterate over the qualifiers and fields in the DFSchema
-    pub fn iter(&self) -> impl Iterator<Item = (Option<&TableReference>, &FieldRef)> {
+    pub fn iter(&self) -> impl Iterator<Item = (Option<&TableReference>, &LogicalFieldRef)> {
         self.field_qualifiers
             .iter()
-            .zip(self.inner.fields().iter())
+            .zip(self.inner.fields.iter())
             .map(|(qualifier, field)| (qualifier.as_ref(), field))
     }
 }
@@ -807,7 +774,7 @@ impl DFSchema {
 impl From<DFSchema> for Schema {
     /// Convert DFSchema into a Schema
     fn from(df_schema: DFSchema) -> Self {
-        let fields: Fields = df_schema.inner.fields.clone();
+        let fields: Fields = df_schema.inner.fields.clone().into();
         Schema::new_with_metadata(fields, df_schema.inner.metadata.clone())
     }
 }
@@ -815,23 +782,29 @@ impl From<DFSchema> for Schema {
 impl From<&DFSchema> for Schema {
     /// Convert DFSchema reference into a Schema
     fn from(df_schema: &DFSchema) -> Self {
-        let fields: Fields = df_schema.inner.fields.clone();
+        let fields: Fields = df_schema.inner.fields.clone().into();
         Schema::new_with_metadata(fields, df_schema.inner.metadata.clone())
     }
 }
 
-/// Allow DFSchema to be converted into an Arrow `&Schema`
-impl AsRef<Schema> for DFSchema {
-    fn as_ref(&self) -> &Schema {
-        self.as_arrow()
+/// Create a `DFSchema` from an Arrow schema
+impl TryFrom<LogicalSchema> for DFSchema {
+    type Error = DataFusionError;
+    fn try_from(schema: LogicalSchema) -> Result<Self, Self::Error> {
+        Self::try_from(Arc::new(schema))
     }
 }
 
-/// Allow DFSchema to be converted into an Arrow `&SchemaRef` (to clone, for
-/// example)
-impl AsRef<SchemaRef> for DFSchema {
-    fn as_ref(&self) -> &SchemaRef {
-        self.inner()
+impl TryFrom<LogicalSchemaRef> for DFSchema {
+    type Error = DataFusionError;
+    fn try_from(schema: LogicalSchemaRef) -> Result<Self, Self::Error> {
+        let field_count = schema.fields.len();
+        let dfschema = Self {
+            inner: schema,
+            field_qualifiers: vec![None; field_count],
+            functional_dependencies: FunctionalDependencies::empty(),
+        };
+        Ok(dfschema)
     }
 }
 
@@ -839,20 +812,14 @@ impl AsRef<SchemaRef> for DFSchema {
 impl TryFrom<Schema> for DFSchema {
     type Error = DataFusionError;
     fn try_from(schema: Schema) -> Result<Self, Self::Error> {
-        Self::try_from(Arc::new(schema))
+        Self::try_from(LogicalSchema::from(schema))
     }
 }
 
 impl TryFrom<SchemaRef> for DFSchema {
     type Error = DataFusionError;
     fn try_from(schema: SchemaRef) -> Result<Self, Self::Error> {
-        let field_count = schema.fields.len();
-        let dfschema = Self {
-            inner: schema,
-            field_qualifiers: vec![None; field_count],
-            functional_dependencies: FunctionalDependencies::empty(),
-        };
-        Ok(dfschema)
+        Self::try_from(schema.as_ref().clone())
     }
 }
 
@@ -884,22 +851,22 @@ where
     }
 }
 
-impl ToDFSchema for Schema {
+impl ToDFSchema for LogicalSchema {
     fn to_dfschema(self) -> Result<DFSchema> {
         DFSchema::try_from(self)
     }
 }
 
-impl ToDFSchema for SchemaRef {
+impl ToDFSchema for LogicalSchemaRef {
     fn to_dfschema(self) -> Result<DFSchema> {
         DFSchema::try_from(self)
     }
 }
 
-impl ToDFSchema for Vec<Field> {
+impl ToDFSchema for Vec<LogicalField> {
     fn to_dfschema(self) -> Result<DFSchema> {
         let field_count = self.len();
-        let schema = Schema {
+        let schema = LogicalSchema {
             fields: self.into(),
             metadata: HashMap::new(),
         };
@@ -936,13 +903,13 @@ pub trait ExprSchema: std::fmt::Debug {
     fn nullable(&self, col: &Column) -> Result<bool>;
 
     /// What is the datatype of this column?
-    fn data_type(&self, col: &Column) -> Result<&DataType>;
+    fn data_type(&self, col: &Column) -> Result<&LogicalType>;
 
     /// Returns the column's optional metadata.
     fn metadata(&self, col: &Column) -> Result<&HashMap<String, String>>;
 
     /// Return the coulmn's datatype and nullability
-    fn data_type_and_nullable(&self, col: &Column) -> Result<(&DataType, bool)>;
+    fn data_type_and_nullable(&self, col: &Column) -> Result<(&LogicalType, bool)>;
 }
 
 // Implement `ExprSchema` for `Arc<DFSchema>`
@@ -951,7 +918,7 @@ impl<P: AsRef<DFSchema> + std::fmt::Debug> ExprSchema for P {
         self.as_ref().nullable(col)
     }
 
-    fn data_type(&self, col: &Column) -> Result<&DataType> {
+    fn data_type(&self, col: &Column) -> Result<&LogicalType> {
         self.as_ref().data_type(col)
     }
 
@@ -959,7 +926,7 @@ impl<P: AsRef<DFSchema> + std::fmt::Debug> ExprSchema for P {
         ExprSchema::metadata(self.as_ref(), col)
     }
 
-    fn data_type_and_nullable(&self, col: &Column) -> Result<(&DataType, bool)> {
+    fn data_type_and_nullable(&self, col: &Column) -> Result<(&LogicalType, bool)> {
         self.as_ref().data_type_and_nullable(col)
     }
 }
@@ -969,7 +936,7 @@ impl ExprSchema for DFSchema {
         Ok(self.field_from_column(col)?.is_nullable())
     }
 
-    fn data_type(&self, col: &Column) -> Result<&DataType> {
+    fn data_type(&self, col: &Column) -> Result<&LogicalType> {
         Ok(self.field_from_column(col)?.data_type())
     }
 
@@ -977,7 +944,7 @@ impl ExprSchema for DFSchema {
         Ok(self.field_from_column(col)?.metadata())
     }
 
-    fn data_type_and_nullable(&self, col: &Column) -> Result<(&DataType, bool)> {
+    fn data_type_and_nullable(&self, col: &Column) -> Result<(&LogicalType, bool)> {
         let field = self.field_from_column(col)?;
         Ok((field.data_type(), field.is_nullable()))
     }
@@ -1028,8 +995,8 @@ impl SchemaExt for Schema {
             .all(|(f1, f2)| {
                 f1.name() == f2.name()
                     && DFSchema::datatype_is_logically_equal(
-                        f1.data_type(),
-                        f2.data_type(),
+                        &f1.data_type().into(),
+                        &f2.data_type().into(),
                     )
             })
     }
@@ -1069,7 +1036,7 @@ mod tests {
             &Schema::new(vec![
                 Field::new("CapitalColumn", DataType::Boolean, true),
                 Field::new("field.with.period", DataType::Boolean, true),
-            ]),
+            ]).into(),
         )?;
 
         // lookup with unqualified name "t1.c0"
@@ -1099,9 +1066,9 @@ mod tests {
     fn test_from_field_specific_qualified_schema() -> Result<()> {
         let schema = DFSchema::from_field_specific_qualified_schema(
             vec![Some("t1".into()), None],
-            &Arc::new(Schema::new(vec![
-                Field::new("c0", DataType::Boolean, true),
-                Field::new("c1", DataType::Boolean, true),
+            &Arc::new(LogicalSchema::new(vec![
+                LogicalField::new("c0", LogicalType::Boolean, true),
+                LogicalField::new("c1", LogicalType::Boolean, true),
             ])),
         )?;
         assert_eq!("fields:[t1.c0, c1], metadata:{}", schema.to_string());
@@ -1114,9 +1081,9 @@ mod tests {
             vec![
                 (
                     Some("t0".into()),
-                    Arc::new(Field::new("c0", DataType::Boolean, true)),
+                    Arc::new(Field::new("c0", DataType::Boolean, true).into()),
                 ),
-                (None, Arc::new(Field::new("c1", DataType::Boolean, true))),
+                (None, Arc::new(Field::new("c1", DataType::Boolean, true).into())),
             ],
             HashMap::new(),
         )?;
@@ -1260,41 +1227,42 @@ mod tests {
             vec![Field::new("c0", DataType::Int64, true)],
             metadata.clone(),
         );
-        let arrow_schema_ref = Arc::new(arrow_schema.clone());
+        let logical_schema = LogicalSchema::from(arrow_schema);
+        let logical_schema_ref = Arc::new(logical_schema.clone());
 
         let df_schema = DFSchema {
-            inner: arrow_schema_ref.clone(),
-            field_qualifiers: vec![None; arrow_schema_ref.fields.len()],
+            inner: logical_schema_ref.clone(),
+            field_qualifiers: vec![None; logical_schema_ref.fields.len()],
             functional_dependencies: FunctionalDependencies::empty(),
         };
         let df_schema_ref = Arc::new(df_schema.clone());
 
         {
-            let arrow_schema = arrow_schema.clone();
-            let arrow_schema_ref = arrow_schema_ref.clone();
+            let logical_schema = logical_schema.clone();
+            let logical_schema_ref = logical_schema_ref.clone();
 
-            assert_eq!(df_schema, arrow_schema.to_dfschema().unwrap());
-            assert_eq!(df_schema, arrow_schema_ref.to_dfschema().unwrap());
+            assert_eq!(df_schema, logical_schema.to_dfschema().unwrap());
+            assert_eq!(df_schema, logical_schema_ref.to_dfschema().unwrap());
         }
 
         {
-            let arrow_schema = arrow_schema.clone();
-            let arrow_schema_ref = arrow_schema_ref.clone();
+            let logical_schema = logical_schema.clone();
+            let logical_schema_ref = logical_schema_ref.clone();
 
-            assert_eq!(df_schema_ref, arrow_schema.to_dfschema_ref().unwrap());
-            assert_eq!(df_schema_ref, arrow_schema_ref.to_dfschema_ref().unwrap());
+            assert_eq!(df_schema_ref, logical_schema.to_dfschema_ref().unwrap());
+            assert_eq!(df_schema_ref, logical_schema_ref.to_dfschema_ref().unwrap());
         }
 
         // Now, consume the refs
-        assert_eq!(df_schema_ref, arrow_schema.to_dfschema_ref().unwrap());
-        assert_eq!(df_schema_ref, arrow_schema_ref.to_dfschema_ref().unwrap());
+        assert_eq!(df_schema_ref, logical_schema.to_dfschema_ref().unwrap());
+        assert_eq!(df_schema_ref, logical_schema_ref.to_dfschema_ref().unwrap());
     }
 
-    fn test_schema_1() -> Schema {
+    fn test_schema_1() -> LogicalSchema {
         Schema::new(vec![
             Field::new("c0", DataType::Boolean, true),
             Field::new("c1", DataType::Boolean, true),
-        ])
+        ]).into()
     }
     #[test]
     fn test_dfschema_to_schema_convertion() {
@@ -1306,7 +1274,7 @@ mod tests {
         b_metadata.insert("key".to_string(), "value".to_string());
         let b_field = Field::new("b", DataType::Int64, false).with_metadata(b_metadata);
 
-        let schema = Arc::new(Schema::new(vec![a_field, b_field]));
+        let schema = LogicalSchemaRef::new(Schema::new(vec![a_field, b_field]).into());
 
         let df_schema = DFSchema {
             inner: schema.clone(),
@@ -1350,10 +1318,10 @@ mod tests {
         Ok(())
     }
 
-    fn test_schema_2() -> Schema {
-        Schema::new(vec![
-            Field::new("c100", DataType::Boolean, true),
-            Field::new("c101", DataType::Boolean, true),
+    fn test_schema_2() -> LogicalSchema {
+        LogicalSchema::new(vec![
+            LogicalField::new("c100", LogicalType::Boolean, true),
+            LogicalField::new("c101", LogicalType::Boolean, true),
         ])
     }
 
diff --git a/datafusion/common/src/lib.rs b/datafusion/common/src/lib.rs
index c275152642f0..7585f1a2c12a 100644
--- a/datafusion/common/src/lib.rs
+++ b/datafusion/common/src/lib.rs
@@ -42,6 +42,7 @@ pub mod stats;
 pub mod test_util;
 pub mod tree_node;
 pub mod utils;
+pub mod logical_type;
 
 /// Reexport arrow crate
 pub use arrow;
diff --git a/datafusion/common/src/logical_type/extension.rs b/datafusion/common/src/logical_type/extension.rs
new file mode 100644
index 000000000000..0332de49f19e
--- /dev/null
+++ b/datafusion/common/src/logical_type/extension.rs
@@ -0,0 +1,289 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::sync::Arc;
+
+use arrow_schema::{DataType, FieldRef, IntervalUnit, TimeUnit};
+
+use crate::logical_type::type_signature::TypeSignature;
+use crate::logical_type::LogicalType;
+
+pub type ExtensionTypeRef = Arc<dyn ExtensionType + Send + Sync>;
+
+pub trait ExtensionType: std::fmt::Debug {
+    fn display_name(&self) -> &str;
+    fn type_signature(&self) -> TypeSignature;
+    fn physical_type(&self) -> DataType;
+
+    fn is_comparable(&self) -> bool;
+    fn is_orderable(&self) -> bool;
+    fn is_numeric(&self) -> bool;
+    fn is_floating(&self) -> bool;
+}
+
+impl ExtensionType for LogicalType {
+    fn display_name(&self) -> &str {
+        use crate::logical_type::LogicalType::*;
+        match self {
+            Null => "Null",
+            Boolean => "Boolean",
+            Int8 => "Int8",
+            Int16 => "Int16",
+            Int32 => "Int32",
+            Int64 => "Int64",
+            UInt8 => "Uint8",
+            UInt16 => "Uint16",
+            UInt32 => "Uint32",
+            UInt64 => "Uint64",
+            Float16 => "Float16",
+            Float32 => "Float16",
+            Float64 => "Float64",
+            Date32 => "Date32",
+            Date64 => "Date64",
+            Time32(_) => "Time32",
+            Time64(_) => "Time64",
+            Timestamp(_, _) => "Timestamp",
+            Duration(_) => "Duration",
+            Interval(_) => "Interval",
+            Binary => "Binary",
+            FixedSizeBinary(_) => "FixedSizeBinary",
+            LargeBinary => "LargeBinary",
+            Utf8 => "Utf8",
+            LargeUtf8 => "LargeUtf8",
+            List(_) => "List",
+            FixedSizeList(_, _) => "FixedSizeList",
+            LargeList(_) => "LargeList",
+            Struct(_) => "Struct",
+            Map(_, _) => "Map",
+            Decimal128(_, _) => "Decimal128",
+            Decimal256(_, _) => "Decimal256",
+            Extension(ext) => ext.display_name(),
+        }
+    }
+
+    fn type_signature(&self) -> TypeSignature {
+        use crate::logical_type::LogicalType::*;
+        fn time_unit_to_param(tu: &TimeUnit) -> &'static str {
+            match tu {
+                TimeUnit::Second => "second",
+                TimeUnit::Millisecond => "millisecond",
+                TimeUnit::Microsecond => "microsecond",
+                TimeUnit::Nanosecond => "nanosecond",
+            }
+        }
+
+        match self {
+            Boolean => TypeSignature::new("boolean"),
+            Int32 => TypeSignature::new("int32"),
+            Int64 => TypeSignature::new("int64"),
+            UInt64 => TypeSignature::new("uint64"),
+            Float32 => TypeSignature::new("float32"),
+            Float64 => TypeSignature::new("float64"),
+            Timestamp(tu, zone) => {
+                let params = if let Some(zone) = zone {
+                    vec![time_unit_to_param(tu).into(), zone.as_ref().into()]
+                } else {
+                    vec![time_unit_to_param(tu).into()]
+                };
+
+                TypeSignature::new_with_params("timestamp", params)
+            }
+            Binary => TypeSignature::new("binary"),
+            Utf8 => TypeSignature::new("string"),
+            Struct(fields) => {
+                let params = fields.iter().map(|f| f.name().into()).collect();
+                TypeSignature::new_with_params("struct", params)
+            }
+            Extension(ext) => ext.type_signature(),
+            Null => TypeSignature::new("null"),
+            Int8 => TypeSignature::new("int8"),
+            Int16 => TypeSignature::new("int16"),
+            UInt8 => TypeSignature::new("uint8"),
+            UInt16 => TypeSignature::new("uint16"),
+            UInt32 => TypeSignature::new("uint32"),
+            Float16 => TypeSignature::new("float16"),
+            Date32 => TypeSignature::new("date_32"),
+            Date64 => TypeSignature::new("date_64"),
+            Time32(tu) => TypeSignature::new_with_params(
+                "time_32",
+                vec![time_unit_to_param(tu).into()],
+            ),
+            Time64(tu) => TypeSignature::new_with_params(
+                "time_64",
+                vec![time_unit_to_param(tu).into()],
+            ),
+            Duration(tu) => TypeSignature::new_with_params(
+                "duration",
+                vec![time_unit_to_param(tu).into()],
+            ),
+            Interval(iu) => {
+                let iu = match iu {
+                    IntervalUnit::YearMonth => "year_month",
+                    IntervalUnit::DayTime => "day_time",
+                    IntervalUnit::MonthDayNano => "month_day_nano",
+                };
+                TypeSignature::new_with_params("interval", vec![iu.into()])
+            }
+            FixedSizeBinary(size) => TypeSignature::new_with_params(
+                "fixed_size_binary",
+                vec![size.to_string().into()],
+            ),
+            LargeBinary => TypeSignature::new("large_binary"),
+            LargeUtf8 => TypeSignature::new("large_utf_8"),
+            List(f) => TypeSignature::new_with_params(
+                "list",
+                vec![f.data_type().display_name().into()],
+            ),
+            FixedSizeList(f, size) => TypeSignature::new_with_params(
+                "fixed_size_list",
+                vec![f.data_type().display_name().into(), size.to_string().into()],
+            ),
+            LargeList(f) => TypeSignature::new_with_params(
+                "large_list",
+                vec![f.data_type().display_name().into()],
+            ),
+            Map(f, b) => TypeSignature::new_with_params(
+                "map",
+                vec![f.data_type().display_name().into(), b.to_string().into()],
+            ),
+            Decimal128(a, b) => TypeSignature::new_with_params(
+                "decimal_128",
+                vec![a.to_string().into(), b.to_string().into()],
+            ),
+            Decimal256(a, b) => TypeSignature::new_with_params(
+                "decimal_256",
+                vec![a.to_string().into(), b.to_string().into()],
+            ),
+        }
+    }
+
+    fn physical_type(&self) -> DataType {
+        use crate::logical_type::LogicalType::*;
+        match self {
+            Boolean => DataType::Boolean,
+            Int32 => DataType::Int32,
+            Int64 => DataType::Int64,
+            UInt64 => DataType::UInt64,
+            Float32 => DataType::Float32,
+            Float64 => DataType::Float64,
+            Timestamp(tu, zone) => DataType::Timestamp(tu.clone(), zone.clone()),
+            Binary => DataType::Binary,
+            Utf8 => DataType::Utf8,
+            Struct(fields) => {
+                let fields = fields
+                    .iter()
+                    .map(|f| FieldRef::new(f.as_ref().clone().into()))
+                    .collect::<Vec<_>>();
+                DataType::Struct(fields.into())
+            }
+            Extension(ext) => ext.physical_type(),
+            Null => DataType::Null,
+            Int8 => DataType::Int8,
+            Int16 => DataType::Int16,
+            UInt8 => DataType::UInt8,
+            UInt16 => DataType::UInt16,
+            UInt32 => DataType::UInt32,
+            Float16 => DataType::Float16,
+            Date32 => DataType::Date32,
+            Date64 => DataType::Date64,
+            Time32(tu) => DataType::Time32(tu.to_owned()),
+            Time64(tu) => DataType::Time64(tu.to_owned()),
+            Duration(tu) => DataType::Duration(tu.to_owned()),
+            Interval(iu) => DataType::Interval(iu.to_owned()),
+            FixedSizeBinary(size) => DataType::FixedSizeBinary(size.to_owned()),
+            LargeBinary => DataType::LargeBinary,
+            LargeUtf8 => DataType::LargeUtf8,
+            List(f) => DataType::List(FieldRef::new(f.as_ref().clone().into())),
+            FixedSizeList(f, size) => DataType::FixedSizeList(FieldRef::new(f.as_ref().clone().into()), size.to_owned()),
+            LargeList(f) => DataType::LargeList(FieldRef::new(f.as_ref().clone().into())),
+            Map(f, b) => DataType::Map(FieldRef::new(f.as_ref().clone().into()), b.to_owned()),
+            Decimal128(a, b) => DataType::Decimal128(a.to_owned(), b.to_owned()),
+            Decimal256(a, b) => DataType::Decimal256(a.to_owned(), b.to_owned()),
+        }
+    }
+
+    fn is_comparable(&self) -> bool {
+        use crate::logical_type::LogicalType::*;
+        match self {
+            Null
+            | Boolean
+            | Int8
+            | Int16
+            | Int32
+            | Int64
+            | UInt8
+            | UInt16
+            | UInt32
+            | UInt64
+            | Float16
+            | Float32
+            | Float64
+            | Date32
+            | Date64
+            | Time32(_)
+            | Time64(_)
+            | Timestamp(_, _)
+            | Duration(_)
+            | Interval(_)
+            | Binary
+            | FixedSizeBinary(_)
+            | LargeBinary
+            | Utf8
+            | LargeUtf8
+            | Decimal128(_, _)
+            | Decimal256(_, _) => true,
+            Extension(ext) => ext.is_comparable(),
+            _ => false,
+        }
+    }
+
+    fn is_orderable(&self) -> bool {
+        todo!()
+    }
+
+    #[inline]
+    fn is_numeric(&self) -> bool {
+        use crate::logical_type::LogicalType::*;
+        match self {
+            UInt8
+            | UInt16
+            | UInt32
+            | UInt64
+            | Int8
+            | Int16
+            | Int32
+            | Int64
+            | Float16
+            | Float32
+            | Float64
+            | Decimal128(_, _)
+            | Decimal256(_, _) => true,
+            Extension(t) => t.is_numeric(),
+            _ => false,
+        }
+    }
+
+    #[inline]
+    fn is_floating(&self) -> bool {
+        use crate::logical_type::LogicalType::*;
+        match self {
+            Float16 | Float32 | Float64 => true,
+            Extension(t) => t.is_floating(),
+            _ => false,
+        }
+    }
+}
diff --git a/datafusion/common/src/logical_type/field.rs b/datafusion/common/src/logical_type/field.rs
new file mode 100644
index 000000000000..3cd6f73fe374
--- /dev/null
+++ b/datafusion/common/src/logical_type/field.rs
@@ -0,0 +1,163 @@
+use std::collections::HashMap;
+use std::hash::{Hash, Hasher};
+use std::sync::Arc;
+use arrow_schema::{DataType, Field};
+use crate::logical_type::extension::ExtensionType;
+use crate::logical_type::fields::LogicalFields;
+use crate::logical_type::LogicalType;
+use crate::logical_type::type_signature::TypeSignature;
+
+pub type LogicalFieldRef = Arc<LogicalField>;
+
+#[derive(Debug, Clone)]
+pub struct LogicalField {
+    name: String,
+    data_type: LogicalType,
+    nullable: bool,
+    metadata: HashMap<String, String>,
+}
+
+impl From<&Field> for LogicalField {
+    fn from(value: &Field) -> Self {
+        Self {
+            name: value.name().clone(),
+            data_type: value.data_type().clone().into(),
+            nullable: value.is_nullable(),
+            metadata: value.metadata().clone()
+        }
+    }
+}
+
+impl From<Field> for LogicalField {
+    fn from(value: Field) -> Self {
+        Self::from(&value)
+    }
+}
+
+impl Into<Field> for LogicalField {
+    fn into(self) -> Field {
+       Field::new(self.name, self.data_type.physical_type(), self.nullable).with_metadata(self.metadata)
+    }
+}
+
+impl PartialEq for LogicalField {
+    fn eq(&self, other: &Self) -> bool {
+        self.name == other.name
+            && self.data_type == other.data_type
+            && self.nullable == other.nullable
+            && self.metadata == other.metadata
+    }
+}
+
+impl Eq for LogicalField {}
+
+impl Hash for LogicalField {
+    fn hash<H: Hasher>(&self, state: &mut H) {
+        self.name.hash(state);
+        self.data_type.hash(state);
+        self.nullable.hash(state);
+
+        // ensure deterministic key order
+        let mut keys: Vec<&String> = self.metadata.keys().collect();
+        keys.sort();
+        for k in keys {
+            k.hash(state);
+            self.metadata.get(k).expect("key valid").hash(state);
+        }
+    }
+}
+
+impl ExtensionType for LogicalField {
+    fn display_name(&self) -> &str {
+       &self.name
+    }
+
+    fn type_signature(&self) -> TypeSignature {
+        TypeSignature::new(self.name())
+    }
+
+    fn physical_type(&self) -> DataType {
+        self.data_type.physical_type()
+    }
+
+    fn is_comparable(&self) -> bool {
+        self.data_type.is_comparable()
+    }
+
+    fn is_orderable(&self) -> bool {
+        self.data_type.is_orderable()
+    }
+
+    fn is_numeric(&self) -> bool {
+        self.data_type.is_numeric()
+    }
+
+    fn is_floating(&self) -> bool {
+       self.data_type.is_floating()
+    }
+}
+
+impl LogicalField {
+    pub fn new(name: impl Into<String>, data_type: LogicalType, nullable: bool) -> Self {
+        LogicalField {
+            name: name.into(),
+            data_type,
+            nullable,
+            metadata: HashMap::default(),
+        }
+    }
+
+    pub fn new_list_field(data_type: LogicalType, nullable: bool) -> Self {
+        Self::new("item", data_type, nullable)
+    }
+
+    pub fn new_struct(name: impl Into<String>, fields: impl Into<LogicalFields>, nullable: bool) -> Self {
+        Self::new(name, LogicalType::Struct(fields.into()), nullable)
+    }
+
+    pub fn name(&self) -> &str {
+        &self.name
+    }
+
+    pub fn data_type(&self) -> &LogicalType {
+        &self.data_type
+    }
+
+    pub fn is_nullable(&self) -> bool {
+        self.nullable
+    }
+
+    pub fn metadata(&self) -> &HashMap<String, String> {
+        &self.metadata
+    }
+
+    #[inline]
+    pub fn with_name(mut self, name: impl Into<String>) -> Self {
+        self.name = name.into();
+        self
+    }
+
+    #[inline]
+    pub fn with_nullable(mut self, nullable: bool) -> Self {
+        self.nullable = nullable;
+        self
+    }
+
+    #[inline]
+    pub fn with_metadata(mut self, metadata: HashMap<String, String>) -> Self {
+        self.metadata = metadata;
+        self
+    }
+
+    #[inline]
+    pub fn with_data_type(mut self, data_type: LogicalType) -> Self {
+        self.data_type = data_type;
+        self
+    }
+}
+
+impl std::fmt::Display for LogicalField {
+    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
+        write!(f, "{self:?}")
+    }
+}
diff --git a/datafusion/common/src/logical_type/fields.rs b/datafusion/common/src/logical_type/fields.rs
new file mode 100644
index 000000000000..456835bc8d9b
--- /dev/null
+++ b/datafusion/common/src/logical_type/fields.rs
@@ -0,0 +1,94 @@
+use std::ops::Deref;
+use std::sync::Arc;
+use arrow_schema::{Field, Fields};
+use crate::logical_type::field::{LogicalField, LogicalFieldRef};
+
+#[derive(Clone, Eq, PartialEq, Hash)]
+pub struct LogicalFields(Arc<[LogicalFieldRef]>);
+
+impl std::fmt::Debug for LogicalFields {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        self.0.as_ref().fmt(f)
+    }
+}
+
+impl From<Fields> for LogicalFields {
+    fn from(value: Fields) -> Self {
+        Self(value.into_iter().map(|v| LogicalFieldRef::new(LogicalField::from(v.as_ref()))).collect())
+    }
+}
+
+impl Into<Fields> for LogicalFields {
+    fn into(self) -> Fields {
+        Fields::from(
+            self.iter()
+                .map(|f| f.as_ref().clone().into())
+                .collect::<Vec<Field>>()
+        )
+    }
+}
+
+impl Default for LogicalFields {
+    fn default() -> Self {
+        Self::empty()
+    }
+}
+
+impl FromIterator<LogicalField> for LogicalFields {
+    fn from_iter<T: IntoIterator<Item=LogicalField>>(iter: T) -> Self {
+        iter.into_iter().map(Arc::new).collect()
+    }
+}
+
+impl FromIterator<LogicalFieldRef> for LogicalFields {
+    fn from_iter<T: IntoIterator<Item=LogicalFieldRef>>(iter: T) -> Self {
+        Self(iter.into_iter().collect())
+    }
+}
+
+impl From<Vec<LogicalField>> for LogicalFields {
+    fn from(value: Vec<LogicalField>) -> Self {
+        value.into_iter().collect()
+    }
+}
+
+impl From<Vec<LogicalFieldRef>> for LogicalFields {
+    fn from(value: Vec<LogicalFieldRef>) -> Self {
+        Self(value.into())
+    }
+}
+
+impl From<&[LogicalFieldRef]> for LogicalFields {
+    fn from(value: &[LogicalFieldRef]) -> Self {
+        Self(value.into())
+    }
+}
+
+impl<const N: usize> From<[LogicalFieldRef; N]> for LogicalFields {
+    fn from(value: [LogicalFieldRef; N]) -> Self {
+        Self(Arc::new(value))
+    }
+}
+
+impl Deref for LogicalFields {
+    type Target = [LogicalFieldRef];
+
+    fn deref(&self) -> &Self::Target {
+        self.0.as_ref()
+    }
+}
+
+impl<'a> IntoIterator for &'a LogicalFields {
+    type Item = &'a LogicalFieldRef;
+    type IntoIter = std::slice::Iter<'a, LogicalFieldRef>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.0.iter()
+    }
+}
+
+impl LogicalFields {
+    pub fn empty() -> Self {
+        Self(Arc::new([]))
+    }
+}
diff --git a/datafusion/common/src/logical_type/mod.rs b/datafusion/common/src/logical_type/mod.rs
new file mode 100644
index 000000000000..fd464411a4ef
--- /dev/null
+++ b/datafusion/common/src/logical_type/mod.rs
@@ -0,0 +1,156 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::{fmt::Display, sync::Arc};
+
+use arrow_schema::{DataType, IntervalUnit, TimeUnit};
+
+use crate::logical_type::extension::{ExtensionType, ExtensionTypeRef};
+use crate::logical_type::field::{LogicalField, LogicalFieldRef};
+use crate::logical_type::fields::LogicalFields;
+
+pub mod type_signature;
+pub mod extension;
+pub mod registry;
+pub mod schema;
+pub mod field;
+pub mod fields;
+
+#[derive(Clone, Debug)]
+pub enum LogicalType {
+    Null,
+    Boolean,
+    Int8,
+    Int16,
+    Int32,
+    Int64,
+    UInt8,
+    UInt16,
+    UInt32,
+    UInt64,
+    Float16,
+    Float32,
+    Float64,
+    Date32,
+    Date64,
+    Time32(TimeUnit),
+    Time64(TimeUnit),
+    Timestamp(TimeUnit, Option<Arc<str>>),
+    Duration(TimeUnit),
+    Interval(IntervalUnit),
+    Binary,
+    FixedSizeBinary(i32),
+    LargeBinary,
+    Utf8,
+    LargeUtf8,
+    List(LogicalFieldRef),
+    FixedSizeList(LogicalFieldRef, i32),
+    LargeList(LogicalFieldRef),
+    Struct(LogicalFields),
+    Map(LogicalFieldRef, bool),
+    Decimal128(u8, i8),
+    Decimal256(u8, i8),
+    Extension(ExtensionTypeRef),
+    // TODO: tbd union
+}
+
+impl PartialEq for LogicalType {
+    fn eq(&self, other: &Self) -> bool {
+        self.type_signature() == other.type_signature()
+    }
+}
+
+impl Eq for LogicalType {}
+
+impl std::hash::Hash for LogicalType {
+    fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
+        self.type_signature().hash(state)
+    }
+}
+
+impl Display for LogicalType {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(f, "{self:?}")
+    }
+}
+
+impl From<&DataType> for LogicalType {
+    fn from(value: &DataType) -> Self {
+        value.clone().into()
+    }
+}
+
+impl From<DataType> for LogicalType {
+    fn from(value: DataType) -> Self {
+        match value {
+            DataType::Null => LogicalType::Null,
+            DataType::Boolean => LogicalType::Boolean,
+            DataType::Int8 => LogicalType::Int8,
+            DataType::Int16 => LogicalType::Int16,
+            DataType::Int32 => LogicalType::Int32,
+            DataType::Int64 => LogicalType::Int64,
+            DataType::UInt8 => LogicalType::UInt8,
+            DataType::UInt16 => LogicalType::UInt16,
+            DataType::UInt32 => LogicalType::UInt32,
+            DataType::UInt64 => LogicalType::UInt64,
+            DataType::Float16 => LogicalType::Float16,
+            DataType::Float32 => LogicalType::Float32,
+            DataType::Float64 => LogicalType::Float64,
+            DataType::Timestamp(tu, z) => LogicalType::Timestamp(tu, z),
+            DataType::Date32 => LogicalType::Date32,
+            DataType::Date64 => LogicalType::Date64,
+            DataType::Time32(tu) => LogicalType::Time32(tu),
+            DataType::Time64(tu) => LogicalType::Time64(tu),
+            DataType::Duration(tu) => LogicalType::Duration(tu),
+            DataType::Interval(iu) => LogicalType::Interval(iu),
+            DataType::Binary | DataType::BinaryView => LogicalType::Binary,
+            DataType::FixedSizeBinary(len) => LogicalType::FixedSizeBinary(len),
+            DataType::LargeBinary => LogicalType::LargeBinary,
+            DataType::Utf8 | DataType::Utf8View => LogicalType::Utf8,
+            DataType::LargeUtf8 => LogicalType::LargeUtf8,
+            DataType::List(f) | DataType::ListView(f) => LogicalType::List(LogicalFieldRef::new(f.as_ref().into())),
+            DataType::FixedSizeList(f, len) => LogicalType::FixedSizeList(LogicalFieldRef::new(f.as_ref().into()), len),
+            DataType::LargeList(f) | DataType::LargeListView(f) => LogicalType::LargeList(LogicalFieldRef::new(f.as_ref().into())),
+            DataType::Struct(fields) => LogicalType::Struct(fields.into()),
+            DataType::Dictionary(_, dt) => dt.as_ref().into(),
+            DataType::Decimal128(p, s) => LogicalType::Decimal128(p, s),
+            DataType::Decimal256(p, s) => LogicalType::Decimal256(p, s),
+            DataType::Map(f, sorted) => LogicalType::Map(LogicalFieldRef::new(f.as_ref().into()), sorted),
+            DataType::RunEndEncoded(_, f) => f.data_type().into(),
+            DataType::Union(_, _) => unimplemented!(), // TODO: tbd union
+        }
+    }
+}
+
+impl LogicalType {
+
+    pub fn new_list(data_type: LogicalType, nullable: bool) -> Self {
+        LogicalType::List(Arc::new(LogicalField::new_list_field(data_type, nullable)))
+    }
+
+    pub fn new_large_list(data_type: LogicalType, nullable: bool) -> Self {
+        LogicalType::LargeList(Arc::new(LogicalField::new_list_field(data_type, nullable)))
+    }
+
+    pub fn new_fixed_size_list(data_type: LogicalType, size: i32, nullable: bool) -> Self {
+        LogicalType::FixedSizeList(Arc::new(LogicalField::new_list_field(data_type, nullable)), size)
+    }
+
+    pub fn is_floating(&self) -> bool {
+        matches!(self, Self::Float16 | Self::Float32 | Self::Float64)
+    }
+}
diff --git a/datafusion/common/src/logical_type/registry.rs b/datafusion/common/src/logical_type/registry.rs
new file mode 100644
index 000000000000..63d25bb23e91
--- /dev/null
+++ b/datafusion/common/src/logical_type/registry.rs
@@ -0,0 +1,51 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::collections::HashMap;
+
+use crate::error::_plan_datafusion_err;
+use crate::logical_type::extension::ExtensionTypeRef;
+use crate::logical_type::type_signature::TypeSignature;
+
+pub trait TypeRegistry {
+    fn register_data_type(
+        &mut self,
+        extension_type: ExtensionTypeRef,
+    ) -> crate::Result<Option<ExtensionTypeRef>>;
+
+    fn data_type(&self, signature: &TypeSignature) -> crate::Result<ExtensionTypeRef>;
+}
+
+
+#[derive(Default, Debug)]
+pub struct MemoryTypeRegistry {
+    types: HashMap<TypeSignature, ExtensionTypeRef>,
+}
+
+impl TypeRegistry for MemoryTypeRegistry {
+    fn register_data_type(&mut self, extension_type: ExtensionTypeRef) -> crate::Result<Option<ExtensionTypeRef>> {
+        Ok(self.types.insert(extension_type.type_signature(), extension_type))
+    }
+
+    fn data_type(&self, signature: &TypeSignature) -> crate::Result<ExtensionTypeRef> {
+        self.types
+            .get(signature)
+            .cloned()
+            .ok_or_else(|| _plan_datafusion_err!("Type with signature {signature:?} not found"))
+    }
+}
+
diff --git a/datafusion/common/src/logical_type/schema.rs b/datafusion/common/src/logical_type/schema.rs
new file mode 100644
index 000000000000..f0c2854b4e64
--- /dev/null
+++ b/datafusion/common/src/logical_type/schema.rs
@@ -0,0 +1,159 @@
+use std::collections::HashMap;
+use std::sync::Arc;
+
+use arrow_schema::Schema;
+
+use crate::logical_type::field::{LogicalField, LogicalFieldRef};
+use crate::logical_type::fields::LogicalFields;
+
+#[derive(Debug, Default)]
+pub struct LogicalSchemaBuilder {
+    fields: Vec<LogicalFieldRef>,
+    metadata: HashMap<String, String>,
+}
+
+impl LogicalSchemaBuilder {
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    pub fn with_capacity(capacity: usize) -> Self {
+        Self {
+            fields: Vec::with_capacity(capacity),
+            metadata: Default::default(),
+        }
+    }
+
+    pub fn push(&mut self, field: impl Into<LogicalFieldRef>) {
+        self.fields.push(field.into())
+    }
+
+    pub fn remove(&mut self, idx: usize) -> LogicalFieldRef {
+        self.fields.remove(idx)
+    }
+
+    pub fn field(&mut self, idx: usize) -> &LogicalFieldRef {
+        &mut self.fields[idx]
+    }
+
+    pub fn field_mut(&mut self, idx: usize) -> &mut LogicalFieldRef {
+        &mut self.fields[idx]
+    }
+
+    pub fn metadata(&mut self) -> &HashMap<String, String> {
+        &self.metadata
+    }
+
+    pub fn metadata_mut(&mut self) -> &mut HashMap<String, String> {
+        &mut self.metadata
+    }
+
+    pub fn reverse(&mut self) {
+        self.fields.reverse();
+    }
+
+    pub fn finish(self) -> LogicalSchema {
+        LogicalSchema {
+            fields: self.fields.into(),
+            metadata: self.metadata,
+        }
+    }
+}
+
+impl From<&LogicalFields> for LogicalSchemaBuilder {
+    fn from(value: &LogicalFields) -> Self {
+        Self {
+            fields: value.to_vec(),
+            metadata: Default::default(),
+        }
+    }
+}
+
+impl From<LogicalFields> for LogicalSchemaBuilder {
+    fn from(value: LogicalFields) -> Self {
+        Self {
+            fields: value.to_vec(),
+            metadata: Default::default(),
+        }
+    }
+}
+
+impl From<&LogicalSchema> for LogicalSchemaBuilder {
+    fn from(value: &LogicalSchema) -> Self {
+        Self::from(value.clone())
+    }
+}
+
+impl From<LogicalSchema> for LogicalSchemaBuilder {
+    fn from(value: LogicalSchema) -> Self {
+        Self {
+            fields: value.fields.to_vec(),
+            metadata: value.metadata,
+        }
+    }
+}
+
+impl Extend<LogicalFieldRef> for LogicalSchemaBuilder {
+    fn extend<T: IntoIterator<Item=LogicalFieldRef>>(&mut self, iter: T) {
+        let iter = iter.into_iter();
+        self.fields.reserve(iter.size_hint().0);
+        for f in iter {
+            self.push(f)
+        }
+    }
+}
+
+impl Extend<LogicalField> for LogicalSchemaBuilder {
+    fn extend<T: IntoIterator<Item=LogicalField>>(&mut self, iter: T) {
+        let iter = iter.into_iter();
+        self.fields.reserve(iter.size_hint().0);
+        for f in iter {
+            self.push(f)
+        }
+    }
+}
+
+pub type LogicalSchemaRef = Arc<LogicalSchema>;
+
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub struct LogicalSchema {
+    pub fields: LogicalFields,
+    pub metadata: HashMap<String, String>,
+}
+
+impl From<Schema> for LogicalSchema {
+    fn from(value: Schema) -> Self {
+        Self {
+            fields: value.fields.into(),
+            metadata: value.metadata,
+        }
+    }
+}
+
+impl LogicalSchema {
+    pub fn new(fields: impl Into<LogicalFields>) -> Self {
+        Self::new_with_metadata(fields, HashMap::new())
+    }
+
+    #[inline]
+    pub fn new_with_metadata(fields: impl Into<LogicalFields>, metadata: HashMap<String, String>) -> Self {
+        Self {
+            fields: fields.into(),
+            metadata,
+        }
+    }
+
+    #[inline]
+    pub fn with_metadata(mut self, metadata: HashMap<String, String>) -> Self {
+        self.metadata = metadata;
+        self
+    }
+
+    pub fn metadata(&self) -> &HashMap<String, String> {
+        &self.metadata
+    }
+
+    pub fn field(&self, i: usize) -> &LogicalFieldRef {
+        &self.fields[i]
+    }
+}
\ No newline at end of file
diff --git a/datafusion/common/src/logical_type/type_signature.rs b/datafusion/common/src/logical_type/type_signature.rs
new file mode 100644
index 000000000000..4b46d040e5c4
--- /dev/null
+++ b/datafusion/common/src/logical_type/type_signature.rs
@@ -0,0 +1,42 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::sync::Arc;
+
+#[derive(Debug, Clone, PartialEq, Eq, Hash)]
+pub struct TypeSignature {
+    // **func_name**(p1, p2)
+    name: Arc<str>,
+    // func_name(**p1**, **p2**)
+    params: Vec<Arc<str>>,
+}
+
+impl TypeSignature {
+    pub fn new(name: impl Into<Arc<str>>) -> Self {
+        Self::new_with_params(name, vec![])
+    }
+
+    pub fn new_with_params(
+        name: impl Into<Arc<str>>,
+        params: Vec<Arc<str>>,
+    ) -> Self {
+        Self {
+            name: name.into(),
+            params,
+        }
+    }
+}
diff --git a/datafusion/common/src/param_value.rs b/datafusion/common/src/param_value.rs
index 8d61bad97b9f..e389d520d834 100644
--- a/datafusion/common/src/param_value.rs
+++ b/datafusion/common/src/param_value.rs
@@ -17,8 +17,8 @@
 
 use crate::error::{_plan_datafusion_err, _plan_err};
 use crate::{Result, ScalarValue};
-use arrow_schema::DataType;
 use std::collections::HashMap;
+use crate::logical_type::LogicalType;
 
 /// The parameter value corresponding to the placeholder
 #[derive(Debug, Clone)]
@@ -31,7 +31,7 @@ pub enum ParamValues {
 
 impl ParamValues {
     /// Verify parameter list length and type
-    pub fn verify(&self, expect: &[DataType]) -> Result<()> {
+    pub fn verify(&self, expect: &[LogicalType]) -> Result<()> {
         match self {
             ParamValues::List(list) => {
                 // Verify if the number of params matches the number of values
@@ -46,7 +46,7 @@ impl ParamValues {
                 // Verify if the types of the params matches the types of the values
                 let iter = expect.iter().zip(list.iter());
                 for (i, (param_type, value)) in iter.enumerate() {
-                    if *param_type != value.data_type() {
+                    if *param_type != value.data_type().into() {
                         return _plan_err!(
                             "Expected parameter of type {:?}, got {:?} at index {}",
                             param_type,
diff --git a/datafusion/common/src/scalar/mod.rs b/datafusion/common/src/scalar/mod.rs
index 5b9c4a223de6..67e959984b3d 100644
--- a/datafusion/common/src/scalar/mod.rs
+++ b/datafusion/common/src/scalar/mod.rs
@@ -54,10 +54,11 @@ use arrow::{
     },
 };
 use arrow_buffer::{IntervalDayTime, IntervalMonthDayNano, ScalarBuffer};
-use arrow_schema::{UnionFields, UnionMode};
+use arrow_schema::{FieldRef, UnionFields, UnionMode};
 
 use half::f16;
 pub use struct_builder::ScalarStructBuilder;
+use crate::logical_type::LogicalType;
 
 /// A dynamically typed, nullable single value.
 ///
@@ -3270,6 +3271,118 @@ impl TryFrom<&DataType> for ScalarValue {
     }
 }
 
+
+impl TryFrom<LogicalType> for ScalarValue {
+    type Error = DataFusionError;
+
+    /// Create a Null instance of ScalarValue for this datatype
+    fn try_from(datatype: LogicalType) -> Result<Self> {
+        (&datatype).try_into()
+    }
+}
+
+impl TryFrom<&LogicalType> for ScalarValue {
+    type Error = DataFusionError;
+
+    /// Create a Null instance of ScalarValue for this datatype
+    fn try_from(data_type: &LogicalType) -> Result<Self> {
+        Ok(match data_type {
+            LogicalType::Boolean => ScalarValue::Boolean(None),
+            LogicalType::Float16 => ScalarValue::Float16(None),
+            LogicalType::Float64 => ScalarValue::Float64(None),
+            LogicalType::Float32 => ScalarValue::Float32(None),
+            LogicalType::Int8 => ScalarValue::Int8(None),
+            LogicalType::Int16 => ScalarValue::Int16(None),
+            LogicalType::Int32 => ScalarValue::Int32(None),
+            LogicalType::Int64 => ScalarValue::Int64(None),
+            LogicalType::UInt8 => ScalarValue::UInt8(None),
+            LogicalType::UInt16 => ScalarValue::UInt16(None),
+            LogicalType::UInt32 => ScalarValue::UInt32(None),
+            LogicalType::UInt64 => ScalarValue::UInt64(None),
+            LogicalType::Decimal128(precision, scale) => {
+                ScalarValue::Decimal128(None, *precision, *scale)
+            }
+            LogicalType::Decimal256(precision, scale) => {
+                ScalarValue::Decimal256(None, *precision, *scale)
+            }
+            LogicalType::Utf8 => ScalarValue::Utf8(None),
+            LogicalType::LargeUtf8 => ScalarValue::LargeUtf8(None),
+            LogicalType::Binary => ScalarValue::Binary(None),
+            LogicalType::FixedSizeBinary(len) => ScalarValue::FixedSizeBinary(*len, None),
+            LogicalType::LargeBinary => ScalarValue::LargeBinary(None),
+            LogicalType::Date32 => ScalarValue::Date32(None),
+            LogicalType::Date64 => ScalarValue::Date64(None),
+            LogicalType::Time32(TimeUnit::Second) => ScalarValue::Time32Second(None),
+            LogicalType::Time32(TimeUnit::Millisecond) => {
+                ScalarValue::Time32Millisecond(None)
+            }
+            LogicalType::Time64(TimeUnit::Microsecond) => {
+                ScalarValue::Time64Microsecond(None)
+            }
+            LogicalType::Time64(TimeUnit::Nanosecond) => ScalarValue::Time64Nanosecond(None),
+            LogicalType::Timestamp(TimeUnit::Second, tz_opt) => {
+                ScalarValue::TimestampSecond(None, tz_opt.clone())
+            }
+            LogicalType::Timestamp(TimeUnit::Millisecond, tz_opt) => {
+                ScalarValue::TimestampMillisecond(None, tz_opt.clone())
+            }
+            LogicalType::Timestamp(TimeUnit::Microsecond, tz_opt) => {
+                ScalarValue::TimestampMicrosecond(None, tz_opt.clone())
+            }
+            LogicalType::Timestamp(TimeUnit::Nanosecond, tz_opt) => {
+                ScalarValue::TimestampNanosecond(None, tz_opt.clone())
+            }
+            LogicalType::Interval(IntervalUnit::YearMonth) => {
+                ScalarValue::IntervalYearMonth(None)
+            }
+            LogicalType::Interval(IntervalUnit::DayTime) => {
+                ScalarValue::IntervalDayTime(None)
+            }
+            LogicalType::Interval(IntervalUnit::MonthDayNano) => {
+                ScalarValue::IntervalMonthDayNano(None)
+            }
+            LogicalType::Duration(TimeUnit::Second) => ScalarValue::DurationSecond(None),
+            LogicalType::Duration(TimeUnit::Millisecond) => {
+                ScalarValue::DurationMillisecond(None)
+            }
+            LogicalType::Duration(TimeUnit::Microsecond) => {
+                ScalarValue::DurationMicrosecond(None)
+            }
+            LogicalType::Duration(TimeUnit::Nanosecond) => {
+                ScalarValue::DurationNanosecond(None)
+            }
+            // `ScalaValue::List` contains single element `ListArray`.
+            LogicalType::List(field_ref) => ScalarValue::List(Arc::new(
+                GenericListArray::new_null(FieldRef::new(field_ref.as_ref().clone().into()), 1),
+            )),
+            // `ScalarValue::LargeList` contains single element `LargeListArray`.
+            LogicalType::LargeList(field_ref) => ScalarValue::LargeList(Arc::new(
+                GenericListArray::new_null(FieldRef::new(field_ref.as_ref().clone().into()), 1),
+            )),
+            // `ScalaValue::FixedSizeList` contains single element `FixedSizeList`.
+            LogicalType::FixedSizeList(field_ref, fixed_length) => {
+                ScalarValue::FixedSizeList(Arc::new(FixedSizeListArray::new_null(
+                    FieldRef::new(field_ref.as_ref().clone().into()),
+                    *fixed_length,
+                    1,
+                )))
+            }
+            LogicalType::Struct(fields) => ScalarValue::Struct(
+                new_null_array(&DataType::Struct(fields.clone().into()), 1)
+                    .as_struct()
+                    .to_owned()
+                    .into(),
+            ),
+            LogicalType::Null => ScalarValue::Null,
+            _ => {
+                return _not_impl_err!(
+                    "Can't create a scalar from data_type \"{data_type:?}\""
+                );
+            }
+        })
+    }
+}
+
 macro_rules! format_option {
     ($F:expr, $EXPR:expr) => {{
         match $EXPR {
diff --git a/datafusion/core/src/dataframe/mod.rs b/datafusion/core/src/dataframe/mod.rs
index 8e55da8c3ad0..afcfe6615c0a 100644
--- a/datafusion/core/src/dataframe/mod.rs
+++ b/datafusion/core/src/dataframe/mod.rs
@@ -58,6 +58,8 @@ use datafusion_expr::{
 use datafusion_functions_aggregate::expr_fn::{avg, count, median, stddev, sum};
 
 use async_trait::async_trait;
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 
 /// Contains options that control how data is
 /// written out from a DataFrame
@@ -666,7 +668,7 @@ impl DataFrame {
                 original_schema_fields
                     .clone()
                     .filter(|f| {
-                        !matches!(f.data_type(), DataType::Binary | DataType::Boolean)
+                        !matches!(f.data_type(), LogicalType::Binary | LogicalType::Boolean)
                     })
                     .map(|f| min(col(f.name())).alias(f.name()))
                     .collect::<Vec<_>>(),
@@ -677,7 +679,7 @@ impl DataFrame {
                 original_schema_fields
                     .clone()
                     .filter(|f| {
-                        !matches!(f.data_type(), DataType::Binary | DataType::Boolean)
+                        !matches!(f.data_type(), LogicalType::Binary | LogicalType::Boolean)
                     })
                     .map(|f| max(col(f.name())).alias(f.name()))
                     .collect::<Vec<_>>(),
@@ -1285,7 +1287,7 @@ impl DataFrame {
         let plan = LogicalPlanBuilder::insert_into(
             self.plan,
             table_name.to_owned(),
-            &arrow_schema,
+            &arrow_schema.into(),
             write_options.overwrite,
         )?
         .build()?;
@@ -1695,6 +1697,7 @@ mod tests {
 
     use arrow::array::{self, Int32Array};
     use datafusion_common::{Constraint, Constraints};
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_common_runtime::SpawnedTask;
     use datafusion_expr::{
         array_agg, cast, create_udf, expr, lit, BuiltInWindowFunction,
@@ -2362,7 +2365,7 @@ mod tests {
         let field = df.schema().field(0);
         // There are two columns named 'c', one from the input of the aggregate and the other from the output.
         // Select should return the column from the output of the aggregate, which is a list.
-        assert!(matches!(field.data_type(), DataType::List(_)));
+        assert!(matches!(field.data_type(), LogicalType::List(_)));
 
         Ok(())
     }
@@ -3169,7 +3172,7 @@ mod tests {
             .await?
             .select_columns(&["c2", "c3"])?
             .limit(0, Some(1))?
-            .with_column("sum", cast(col("c2") + col("c3"), DataType::Int64))?;
+            .with_column("sum", cast(col("c2") + col("c3"), LogicalType::Int64))?;
 
         let df_results = df.clone().collect().await?;
         df.clone().show().await?;
@@ -3271,7 +3274,7 @@ mod tests {
             .await?
             .select_columns(&["c2", "c3"])?
             .limit(0, Some(1))?
-            .with_column("sum", cast(col("c2") + col("c3"), DataType::Int64))?;
+            .with_column("sum", cast(col("c2") + col("c3"), LogicalType::Int64))?;
 
         let cached_df = df.clone().cache().await?;
 
diff --git a/datafusion/core/src/datasource/listing/helpers.rs b/datafusion/core/src/datasource/listing/helpers.rs
index 822a66783819..8236f8f06c71 100644
--- a/datafusion/core/src/datasource/listing/helpers.rs
+++ b/datafusion/core/src/datasource/listing/helpers.rs
@@ -44,6 +44,7 @@ use datafusion_expr::{Expr, Volatility};
 use datafusion_physical_expr::create_physical_expr;
 use object_store::path::Path;
 use object_store::{ObjectMeta, ObjectStore};
+use datafusion_common::logical_type::field::LogicalField;
 
 /// Check whether the given expression can be resolved using only the columns `col_names`.
 /// This means that if this function returns true:
@@ -264,7 +265,7 @@ async fn prune_partitions(
     let df_schema = DFSchema::from_unqualifed_fields(
         partition_cols
             .iter()
-            .map(|(n, d)| Field::new(n, d.clone(), true))
+            .map(|(n, d)| LogicalField::new(n, d.clone().into(), true))
             .collect(),
         Default::default(),
     )?;
diff --git a/datafusion/core/src/datasource/listing/table.rs b/datafusion/core/src/datasource/listing/table.rs
index 74aca82b3ee6..ffa0013b31cb 100644
--- a/datafusion/core/src/datasource/listing/table.rs
+++ b/datafusion/core/src/datasource/listing/table.rs
@@ -55,6 +55,7 @@ use async_trait::async_trait;
 use futures::{future, stream, StreamExt, TryStreamExt};
 use itertools::Itertools;
 use object_store::ObjectStore;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 /// Configuration for creating a [`ListingTable`]
 #[derive(Debug, Clone)]
@@ -788,7 +789,7 @@ impl TableProvider for ListingTable {
 
         let filters = if let Some(expr) = conjunction(filters.to_vec()) {
             // NOTE: Use the table schema (NOT file schema) here because `expr` may contain references to partition columns.
-            let table_df_schema = self.table_schema.as_ref().clone().to_dfschema()?;
+            let table_df_schema = LogicalSchema::from(self.table_schema.as_ref().clone()).to_dfschema()?;
             let filters =
                 create_physical_expr(&expr, &table_df_schema, state.execution_props())?;
             Some(filters)
@@ -1877,7 +1878,7 @@ mod tests {
         // Therefore, we will have 8 partitions in the final plan.
         // Create an insert plan to insert the source data into the initial table
         let insert_into_table =
-            LogicalPlanBuilder::insert_into(scan_plan, "t", &schema, false)?.build()?;
+            LogicalPlanBuilder::insert_into(scan_plan, "t", &schema.as_ref().clone().into(), false)?.build()?;
         // Create a physical plan from the insert plan
         let plan = session_ctx
             .state()
diff --git a/datafusion/core/src/datasource/memory.rs b/datafusion/core/src/datasource/memory.rs
index aab42285a0b2..3126e8dee5de 100644
--- a/datafusion/core/src/datasource/memory.rs
+++ b/datafusion/core/src/datasource/memory.rs
@@ -624,7 +624,7 @@ mod tests {
         let scan_plan = LogicalPlanBuilder::scan("source", source, None)?.build()?;
         // Create an insert plan to insert the source data into the initial table
         let insert_into_table =
-            LogicalPlanBuilder::insert_into(scan_plan, "t", &schema, false)?.build()?;
+            LogicalPlanBuilder::insert_into(scan_plan, "t", &schema.as_ref().clone().into(), false)?.build()?;
         // Create a physical plan from the insert plan
         let plan = session_ctx
             .state()
diff --git a/datafusion/core/src/datasource/physical_plan/file_scan_config.rs b/datafusion/core/src/datasource/physical_plan/file_scan_config.rs
index f5d3c7a6410d..f09e77a9a8be 100644
--- a/datafusion/core/src/datasource/physical_plan/file_scan_config.rs
+++ b/datafusion/core/src/datasource/physical_plan/file_scan_config.rs
@@ -626,7 +626,6 @@ fn create_output_array(
 #[cfg(test)]
 mod tests {
     use arrow_array::Int32Array;
-
     use super::*;
     use crate::{test::columns, test_util::aggr_test_schema};
 
diff --git a/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs b/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs
index f9cce5f783ff..b73bbd8dad66 100644
--- a/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs
+++ b/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs
@@ -425,6 +425,9 @@ mod test {
     use parquet::file::reader::{FileReader, SerializedFileReader};
     use rand::prelude::*;
 
+    use datafusion_common::logical_type::LogicalType;
+
+
     // We should ignore predicate that read non-primitive columns
     #[test]
     fn test_filter_candidate_builder_ignore_complex_types() {
@@ -471,10 +474,10 @@ mod test {
         ]);
 
         // The parquet file with `file_schema` just has `bigint_col` and `float_col` column, and don't have the `int_col`
-        let expr = col("bigint_col").eq(cast(col("int_col"), DataType::Int64));
+        let expr = col("bigint_col").eq(cast(col("int_col"), LogicalType::Int64));
         let expr = logical2physical(&expr, &table_schema);
         let expected_candidate_expr =
-            col("bigint_col").eq(cast(lit(ScalarValue::Int32(None)), DataType::Int64));
+            col("bigint_col").eq(cast(lit(ScalarValue::Int32(None)), LogicalType::Int64));
         let expected_candidate_expr =
             logical2physical(&expected_candidate_expr, &table_schema);
 
diff --git a/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs b/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs
index 9bc79805746f..87d64c4a43ba 100644
--- a/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs
+++ b/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs
@@ -411,9 +411,8 @@ mod tests {
     use crate::datasource::physical_plan::parquet::reader::ParquetFileReader;
     use crate::physical_plan::metrics::ExecutionPlanMetricsSet;
 
-    use arrow::datatypes::DataType::Decimal128;
     use arrow::datatypes::{DataType, Field};
-    use datafusion_common::Result;
+    use datafusion_common::{Result, logical_type::LogicalType::*};
     use datafusion_expr::{cast, col, lit, Expr};
     use datafusion_physical_expr::planner::logical2physical;
 
@@ -819,7 +818,7 @@ mod tests {
             .with_scale(0)
             .with_precision(9);
         let schema_descr = get_test_schema_descr(vec![field]);
-        let expr = cast(col("c1"), DataType::Decimal128(11, 2)).gt(cast(
+        let expr = cast(col("c1"), Decimal128(11, 2)).gt(cast(
             lit(ScalarValue::Decimal128(Some(500), 5, 2)),
             Decimal128(11, 2),
         ));
@@ -936,7 +935,7 @@ mod tests {
             .with_byte_len(16);
         let schema_descr = get_test_schema_descr(vec![field]);
         // cast the type of c1 to decimal(28,3)
-        let left = cast(col("c1"), DataType::Decimal128(28, 3));
+        let left = cast(col("c1"), Decimal128(28, 3));
         let expr = left.eq(lit(ScalarValue::Decimal128(Some(100000), 28, 3)));
         let expr = logical2physical(&expr, &schema);
         let pruning_predicate = PruningPredicate::try_new(expr, schema.clone()).unwrap();
@@ -1010,7 +1009,7 @@ mod tests {
             .with_byte_len(16);
         let schema_descr = get_test_schema_descr(vec![field]);
         // cast the type of c1 to decimal(28,3)
-        let left = cast(col("c1"), DataType::Decimal128(28, 3));
+        let left = cast(col("c1"), Decimal128(28, 3));
         let expr = left.eq(lit(ScalarValue::Decimal128(Some(100000), 28, 3)));
         let expr = logical2physical(&expr, &schema);
         let pruning_predicate = PruningPredicate::try_new(expr, schema.clone()).unwrap();
diff --git a/datafusion/core/src/execution/session_state.rs b/datafusion/core/src/execution/session_state.rs
index 2b7867e72046..6068b89cb4be 100644
--- a/datafusion/core/src/execution/session_state.rs
+++ b/datafusion/core/src/execution/session_state.rs
@@ -42,7 +42,7 @@ use crate::physical_optimizer::optimizer::PhysicalOptimizer;
 use crate::physical_optimizer::PhysicalOptimizerRule;
 use crate::physical_planner::{DefaultPhysicalPlanner, PhysicalPlanner};
 use crate::{functions, functions_aggregate};
-use arrow_schema::{DataType, SchemaRef};
+use arrow_schema::{SchemaRef};
 use async_trait::async_trait;
 use chrono::{DateTime, Utc};
 use datafusion_common::alias::AliasGenerator;
@@ -84,6 +84,7 @@ use std::fmt::Debug;
 use std::sync::Arc;
 use url::Url;
 use uuid::Uuid;
+use datafusion_common::logical_type::LogicalType;
 
 /// Execution context for registering data sources and executing queries.
 /// See [`SessionContext`] for a higher level API.
@@ -1001,7 +1002,7 @@ impl<'a> ContextProvider for SessionContextProvider<'a> {
         self.state.window_functions().get(name).cloned()
     }
 
-    fn get_variable_type(&self, variable_names: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, variable_names: &[String]) -> Option<LogicalType> {
         if variable_names.is_empty() {
             return None;
         }
@@ -1218,7 +1219,7 @@ impl<'a> SessionSimplifyProvider<'a> {
 
 impl<'a> SimplifyInfo for SessionSimplifyProvider<'a> {
     fn is_boolean_type(&self, expr: &Expr) -> datafusion_common::Result<bool> {
-        Ok(expr.get_type(self.df_schema)? == DataType::Boolean)
+        Ok(expr.get_type(self.df_schema)? == LogicalType::Boolean)
     }
 
     fn nullable(&self, expr: &Expr) -> datafusion_common::Result<bool> {
@@ -1229,7 +1230,7 @@ impl<'a> SimplifyInfo for SessionSimplifyProvider<'a> {
         self.state.execution_props()
     }
 
-    fn get_data_type(&self, expr: &Expr) -> datafusion_common::Result<DataType> {
+    fn get_data_type(&self, expr: &Expr) -> datafusion_common::Result<LogicalType> {
         expr.get_type(self.df_schema)
     }
 }
diff --git a/datafusion/core/src/physical_optimizer/pruning.rs b/datafusion/core/src/physical_optimizer/pruning.rs
index e8f2f34abda0..8624a80bfce3 100644
--- a/datafusion/core/src/physical_optimizer/pruning.rs
+++ b/datafusion/core/src/physical_optimizer/pruning.rs
@@ -1571,6 +1571,7 @@ mod tests {
     use datafusion_expr::expr::InList;
     use datafusion_expr::{cast, is_null, try_cast, Expr};
     use datafusion_physical_expr::planner::logical2physical;
+    use datafusion_common::logical_type::LogicalType;
 
     #[derive(Debug, Default)]
     /// Mock statistic provider for tests
@@ -2607,13 +2608,13 @@ mod tests {
 
         // test cast(c1 as int64) = 1
         // test column on the left
-        let expr = cast(col("c1"), DataType::Int64).eq(lit(ScalarValue::Int64(Some(1))));
+        let expr = cast(col("c1"), LogicalType::Int64).eq(lit(ScalarValue::Int64(Some(1))));
         let predicate_expr =
             test_build_predicate_expression(&expr, &schema, &mut RequiredColumns::new());
         assert_eq!(predicate_expr.to_string(), expected_expr);
 
         // test column on the right
-        let expr = lit(ScalarValue::Int64(Some(1))).eq(cast(col("c1"), DataType::Int64));
+        let expr = lit(ScalarValue::Int64(Some(1))).eq(cast(col("c1"), LogicalType::Int64));
         let predicate_expr =
             test_build_predicate_expression(&expr, &schema, &mut RequiredColumns::new());
         assert_eq!(predicate_expr.to_string(), expected_expr);
@@ -2625,14 +2626,14 @@ mod tests {
 
         // test column on the left
         let expr =
-            try_cast(col("c1"), DataType::Int64).gt(lit(ScalarValue::Int64(Some(1))));
+            try_cast(col("c1"), LogicalType::Int64).gt(lit(ScalarValue::Int64(Some(1))));
         let predicate_expr =
             test_build_predicate_expression(&expr, &schema, &mut RequiredColumns::new());
         assert_eq!(predicate_expr.to_string(), expected_expr);
 
         // test column on the right
         let expr =
-            lit(ScalarValue::Int64(Some(1))).lt(try_cast(col("c1"), DataType::Int64));
+            lit(ScalarValue::Int64(Some(1))).lt(try_cast(col("c1"), LogicalType::Int64));
         let predicate_expr =
             test_build_predicate_expression(&expr, &schema, &mut RequiredColumns::new());
         assert_eq!(predicate_expr.to_string(), expected_expr);
@@ -2645,7 +2646,7 @@ mod tests {
         let schema = Schema::new(vec![Field::new("c1", DataType::Int32, false)]);
         // test cast(c1 as int64) in int64(1, 2, 3)
         let expr = Expr::InList(InList::new(
-            Box::new(cast(col("c1"), DataType::Int64)),
+            Box::new(cast(col("c1"), LogicalType::Int64)),
             vec![
                 lit(ScalarValue::Int64(Some(1))),
                 lit(ScalarValue::Int64(Some(2))),
@@ -2670,7 +2671,7 @@ mod tests {
         assert_eq!(predicate_expr.to_string(), expected_expr);
 
         let expr = Expr::InList(InList::new(
-            Box::new(cast(col("c1"), DataType::Int64)),
+            Box::new(cast(col("c1"), LogicalType::Int64)),
             vec![
                 lit(ScalarValue::Int64(Some(1))),
                 lit(ScalarValue::Int64(Some(2))),
@@ -2724,7 +2725,7 @@ mod tests {
 
         prune_with_expr(
             // with cast column to other type
-            cast(col("s1"), DataType::Decimal128(14, 3))
+            cast(col("s1"), LogicalType::Decimal128(14, 3))
                 .gt(lit(ScalarValue::Decimal128(Some(5000), 14, 3))),
             &schema,
             &TestStatistics::new().with(
@@ -2739,7 +2740,7 @@ mod tests {
 
         prune_with_expr(
             // with try cast column to other type
-            try_cast(col("s1"), DataType::Decimal128(14, 3))
+            try_cast(col("s1"), LogicalType::Decimal128(14, 3))
                 .gt(lit(ScalarValue::Decimal128(Some(5000), 14, 3))),
             &schema,
             &TestStatistics::new().with(
@@ -2826,7 +2827,7 @@ mod tests {
 
         prune_with_expr(
             // filter with cast
-            cast(col("s2"), DataType::Int64).gt(lit(ScalarValue::Int64(Some(5)))),
+            cast(col("s2"), LogicalType::Int64).gt(lit(ScalarValue::Int64(Some(5)))),
             &schema,
             &statistics,
             &[false, true, true, true],
@@ -3054,7 +3055,7 @@ mod tests {
 
         prune_with_expr(
             // cast(i as utf8) <= 0
-            cast(col("i"), DataType::Utf8).lt_eq(lit("0")),
+            cast(col("i"), LogicalType::Utf8).lt_eq(lit("0")),
             &schema,
             &statistics,
             expected_ret,
@@ -3062,7 +3063,7 @@ mod tests {
 
         prune_with_expr(
             // try_cast(i as utf8) <= 0
-            try_cast(col("i"), DataType::Utf8).lt_eq(lit("0")),
+            try_cast(col("i"), LogicalType::Utf8).lt_eq(lit("0")),
             &schema,
             &statistics,
             expected_ret,
@@ -3070,7 +3071,7 @@ mod tests {
 
         prune_with_expr(
             // cast(-i as utf8) >= 0
-            cast(Expr::Negative(Box::new(col("i"))), DataType::Utf8).gt_eq(lit("0")),
+            cast(Expr::Negative(Box::new(col("i"))), LogicalType::Utf8).gt_eq(lit("0")),
             &schema,
             &statistics,
             expected_ret,
@@ -3078,7 +3079,7 @@ mod tests {
 
         prune_with_expr(
             // try_cast(-i as utf8) >= 0
-            try_cast(Expr::Negative(Box::new(col("i"))), DataType::Utf8).gt_eq(lit("0")),
+            try_cast(Expr::Negative(Box::new(col("i"))), LogicalType::Utf8).gt_eq(lit("0")),
             &schema,
             &statistics,
             expected_ret,
@@ -3119,14 +3120,14 @@ mod tests {
         let expected_ret = &[true, false, false, true, false];
 
         prune_with_expr(
-            cast(col("i"), DataType::Int64).eq(lit(0i64)),
+            cast(col("i"), LogicalType::Int64).eq(lit(0i64)),
             &schema,
             &statistics,
             expected_ret,
         );
 
         prune_with_expr(
-            try_cast(col("i"), DataType::Int64).eq(lit(0i64)),
+            try_cast(col("i"), LogicalType::Int64).eq(lit(0i64)),
             &schema,
             &statistics,
             expected_ret,
@@ -3149,7 +3150,7 @@ mod tests {
         let expected_ret = &[true, true, true, true, true];
 
         prune_with_expr(
-            cast(col("i"), DataType::Utf8).eq(lit("0")),
+            cast(col("i"), LogicalType::Utf8).eq(lit("0")),
             &schema,
             &statistics,
             expected_ret,
@@ -3304,7 +3305,7 @@ mod tests {
 
         prune_with_expr(
             // i > int64(0)
-            col("i").gt(cast(lit(ScalarValue::Int64(Some(0))), DataType::Int32)),
+            col("i").gt(cast(lit(ScalarValue::Int64(Some(0))), LogicalType::Int32)),
             &schema,
             &statistics,
             expected_ret,
@@ -3312,7 +3313,7 @@ mod tests {
 
         prune_with_expr(
             // cast(i as int64) > int64(0)
-            cast(col("i"), DataType::Int64).gt(lit(ScalarValue::Int64(Some(0)))),
+            cast(col("i"), LogicalType::Int64).gt(lit(ScalarValue::Int64(Some(0)))),
             &schema,
             &statistics,
             expected_ret,
@@ -3320,7 +3321,7 @@ mod tests {
 
         prune_with_expr(
             // try_cast(i as int64) > int64(0)
-            try_cast(col("i"), DataType::Int64).gt(lit(ScalarValue::Int64(Some(0)))),
+            try_cast(col("i"), LogicalType::Int64).gt(lit(ScalarValue::Int64(Some(0)))),
             &schema,
             &statistics,
             expected_ret,
@@ -3328,7 +3329,7 @@ mod tests {
 
         prune_with_expr(
             // `-cast(i as int64) < 0` convert to `cast(i as int64) > -0`
-            Expr::Negative(Box::new(cast(col("i"), DataType::Int64)))
+            Expr::Negative(Box::new(cast(col("i"), LogicalType::Int64)))
                 .lt(lit(ScalarValue::Int64(Some(0)))),
             &schema,
             &statistics,
@@ -3357,7 +3358,7 @@ mod tests {
         assert_eq!(result_right.to_string(), right_input.to_string());
 
         // cast op lit
-        let left_input = cast(col("a"), DataType::Decimal128(20, 3));
+        let left_input = cast(col("a"), LogicalType::Decimal128(20, 3));
         let left_input = logical2physical(&left_input, &schema);
         let right_input = lit(ScalarValue::Decimal128(Some(12), 20, 3));
         let right_input = logical2physical(&right_input, &schema);
@@ -3372,7 +3373,7 @@ mod tests {
         assert_eq!(result_right.to_string(), right_input.to_string());
 
         // try_cast op lit
-        let left_input = try_cast(col("a"), DataType::Int64);
+        let left_input = try_cast(col("a"), LogicalType::Int64);
         let left_input = logical2physical(&left_input, &schema);
         let right_input = lit(ScalarValue::Int64(Some(12)));
         let right_input = logical2physical(&right_input, &schema);
@@ -3391,7 +3392,7 @@ mod tests {
         // this cast is not supported
         let schema = Schema::new(vec![Field::new("a", DataType::Utf8, true)]);
         let df_schema = DFSchema::try_from(schema.clone()).unwrap();
-        let left_input = cast(col("a"), DataType::Int64);
+        let left_input = cast(col("a"), LogicalType::Int64);
         let left_input = logical2physical(&left_input, &schema);
         let right_input = lit(ScalarValue::Int64(Some(12)));
         let right_input = logical2physical(&right_input, &schema);
diff --git a/datafusion/core/src/physical_planner.rs b/datafusion/core/src/physical_planner.rs
index 5b8501baaad8..e971c909a5c2 100644
--- a/datafusion/core/src/physical_planner.rs
+++ b/datafusion/core/src/physical_planner.rs
@@ -2232,6 +2232,8 @@ mod tests {
     use arrow::array::{ArrayRef, DictionaryArray, Int32Array};
     use arrow::datatypes::{DataType, Field, Int32Type};
     use datafusion_common::{assert_contains, DFSchemaRef, TableReference};
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_execution::runtime_env::RuntimeEnv;
     use datafusion_execution::TaskContext;
     use datafusion_expr::{col, lit, LogicalPlanBuilder, UserDefinedLogicalNodeCore};
@@ -2474,12 +2476,11 @@ mod tests {
         let expected_error: &str = "Error during planning: \
             Extension planner for NoOp created an ExecutionPlan with mismatched schema. \
             LogicalPlan schema: \
-            DFSchema { inner: Schema { fields: \
-                [Field { name: \"a\", \
+            DFSchema { inner: LogicalSchema { fields: \
+                [LogicalField { name: \"a\", \
                 data_type: Int32, \
                 nullable: false, \
-                dict_id: 0, \
-                dict_is_ordered: false, metadata: {} }], \
+                metadata: {} }], \
                 metadata: {} }, field_qualifiers: [None], \
                 functional_dependencies: FunctionalDependencies { deps: [] } }, \
             ExecutionPlan schema: Schema { fields: \
@@ -2753,7 +2754,7 @@ mod tests {
             Self {
                 schema: DFSchemaRef::new(
                     DFSchema::from_unqualifed_fields(
-                        vec![Field::new("a", DataType::Int32, false)].into(),
+                        vec![LogicalField::new("a", LogicalType::Int32, false)].into(),
                         HashMap::new(),
                     )
                     .unwrap(),
diff --git a/datafusion/core/src/test/mod.rs b/datafusion/core/src/test/mod.rs
index e8550a79cb0e..1212b572df3e 100644
--- a/datafusion/core/src/test/mod.rs
+++ b/datafusion/core/src/test/mod.rs
@@ -206,7 +206,7 @@ pub fn assert_fields_eq(plan: &LogicalPlan, expected: Vec<&str>) {
         .schema()
         .fields()
         .iter()
-        .map(|f| f.name().clone())
+        .map(|f| f.name().to_string())
         .collect();
     assert_eq!(actual, expected);
 }
diff --git a/datafusion/core/src/test/variable.rs b/datafusion/core/src/test/variable.rs
index 38207b42cb7b..7cf5a7f3ec2b 100644
--- a/datafusion/core/src/test/variable.rs
+++ b/datafusion/core/src/test/variable.rs
@@ -20,7 +20,7 @@
 use crate::error::Result;
 use crate::scalar::ScalarValue;
 use crate::variable::VarProvider;
-use arrow::datatypes::DataType;
+use datafusion_common::logical_type::LogicalType;
 
 /// System variable
 #[derive(Default, Debug)]
@@ -40,8 +40,8 @@ impl VarProvider for SystemVar {
         Ok(ScalarValue::from(s))
     }
 
-    fn get_type(&self, _: &[String]) -> Option<DataType> {
-        Some(DataType::Utf8)
+    fn get_type(&self, _: &[String]) -> Option<LogicalType> {
+        Some(LogicalType::Utf8)
     }
 }
 
@@ -67,11 +67,11 @@ impl VarProvider for UserDefinedVar {
         }
     }
 
-    fn get_type(&self, var_names: &[String]) -> Option<DataType> {
+    fn get_type(&self, var_names: &[String]) -> Option<LogicalType> {
         if var_names[0] != "@integer" {
-            Some(DataType::Utf8)
+            Some(LogicalType::Utf8)
         } else {
-            Some(DataType::Int32)
+            Some(LogicalType::Int32)
         }
     }
 }
diff --git a/datafusion/core/src/test_util/parquet.rs b/datafusion/core/src/test_util/parquet.rs
index 9f06ad9308ab..e8e33badc0af 100644
--- a/datafusion/core/src/test_util/parquet.rs
+++ b/datafusion/core/src/test_util/parquet.rs
@@ -42,6 +42,7 @@ use object_store::path::Path;
 use object_store::ObjectMeta;
 use parquet::arrow::ArrowWriter;
 use parquet::file::properties::WriterProperties;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 ///  a ParquetFile that has been created for testing.
 pub struct TestParquetFile {
@@ -153,7 +154,7 @@ impl TestParquetFile {
                     extensions: None,
                 });
 
-        let df_schema = self.schema.clone().to_dfschema_ref()?;
+        let df_schema = LogicalSchema::from(self.schema.as_ref().clone()).to_dfschema_ref()?;
 
         // run coercion on the filters to coerce types etc.
         let props = ExecutionProps::new();
diff --git a/datafusion/core/tests/dataframe/dataframe_functions.rs b/datafusion/core/tests/dataframe/dataframe_functions.rs
index 1c55c48fea40..b1d615405cac 100644
--- a/datafusion/core/tests/dataframe/dataframe_functions.rs
+++ b/datafusion/core/tests/dataframe/dataframe_functions.rs
@@ -31,6 +31,7 @@ use datafusion::prelude::*;
 
 use datafusion::assert_batches_eq;
 use datafusion_common::{DFSchema, ScalarValue};
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::expr::Alias;
 use datafusion_expr::ExprSchemable;
 use datafusion_functions_aggregate::expr_fn::{approx_median, approx_percentile_cont};
@@ -376,7 +377,7 @@ async fn test_fn_approx_percentile_cont() -> Result<()> {
 
     // the arg2 parameter is a complex expr, but it can be evaluated to the literal value
     let alias_expr = Expr::Alias(Alias::new(
-        cast(lit(0.5), DataType::Float32),
+        cast(lit(0.5), LogicalType::Float32),
         None::<&str>,
         "arg_2".to_string(),
     ));
@@ -949,7 +950,7 @@ async fn test_fn_substr() -> Result<()> {
 
 #[tokio::test]
 async fn test_cast() -> Result<()> {
-    let expr = cast(col("b"), DataType::Float64);
+    let expr = cast(col("b"), LogicalType::Float64);
     let expected = [
         "+--------+",
         "| test.b |",
@@ -1052,7 +1053,7 @@ async fn test_fn_decode() -> Result<()> {
     let expr = decode(encode(col("a"), lit("hex")), lit("hex"))
         // need to cast to utf8 otherwise the default display of binary array is hex
         // so it looks like nothing is done
-        .cast_to(&DataType::Utf8, &df_schema)?;
+        .cast_to(&LogicalType::Utf8, &df_schema)?;
 
     let expected = [
         "+------------------------------------------------+",
diff --git a/datafusion/core/tests/dataframe/mod.rs b/datafusion/core/tests/dataframe/mod.rs
index c3bc2fcca2b5..d7228dcf3689 100644
--- a/datafusion/core/tests/dataframe/mod.rs
+++ b/datafusion/core/tests/dataframe/mod.rs
@@ -47,6 +47,7 @@ use datafusion::prelude::{CsvReadOptions, ParquetReadOptions};
 use datafusion::test_util::{parquet_test_data, populate_csv_partitions};
 use datafusion::{assert_batches_eq, assert_batches_sorted_eq};
 use datafusion_common::{assert_contains, DataFusionError, ScalarValue, UnnestOptions};
+use datafusion_common::logical_type::LogicalType;
 use datafusion_execution::config::SessionConfig;
 use datafusion_execution::runtime_env::RuntimeEnv;
 use datafusion_expr::expr::{GroupingSet, Sort};
@@ -256,7 +257,7 @@ async fn test_count_wildcard_on_where_scalar_subquery() -> Result<()> {
             scalar_subquery(Arc::new(
                 ctx.table("t2")
                     .await?
-                    .filter(out_ref_col(DataType::UInt32, "t1.a").eq(col("t2.a")))?
+                    .filter(out_ref_col(LogicalType::UInt32, "t1.a").eq(col("t2.a")))?
                     .aggregate(vec![], vec![count(wildcard())])?
                     .select(vec![col(count(wildcard()).to_string())])?
                     .into_unoptimized_plan(),
@@ -746,8 +747,8 @@ async fn join_with_alias_filter() -> Result<()> {
 
     // filter: t1.a + CAST(Int64(1), UInt32) = t2.a + CAST(Int64(2), UInt32) as t1.a + 1 = t2.a + 2
     let filter = Expr::eq(
-        col("t1.a") + lit(3i64).cast_to(&DataType::UInt32, &t1_schema)?,
-        col("t2.a") + lit(1i32).cast_to(&DataType::UInt32, &t2_schema)?,
+        col("t1.a") + lit(3i64).cast_to(&LogicalType::UInt32, &t1_schema)?,
+        col("t2.a") + lit(1i32).cast_to(&LogicalType::UInt32, &t2_schema)?,
     )
     .alias("t1.b + 1 = t2.a + 2");
 
@@ -1622,7 +1623,7 @@ async fn consecutive_projection_same_schema() -> Result<()> {
 
     // Add `t` column full of nulls
     let df = df
-        .with_column("t", cast(Expr::Literal(ScalarValue::Null), DataType::Int32))
+        .with_column("t", cast(Expr::Literal(ScalarValue::Null), LogicalType::Int32))
         .unwrap();
     df.clone().show().await.unwrap();
 
@@ -1925,8 +1926,8 @@ impl VarProvider for HardcodedIntProvider {
         Ok(ScalarValue::Int64(Some(1234)))
     }
 
-    fn get_type(&self, _: &[String]) -> Option<DataType> {
-        Some(DataType::Int64)
+    fn get_type(&self, _: &[String]) -> Option<LogicalType> {
+        Some(LogicalType::Int64)
     }
 }
 
diff --git a/datafusion/core/tests/expr_api/parse_sql_expr.rs b/datafusion/core/tests/expr_api/parse_sql_expr.rs
index 991579b5a350..e082aaed322b 100644
--- a/datafusion/core/tests/expr_api/parse_sql_expr.rs
+++ b/datafusion/core/tests/expr_api/parse_sql_expr.rs
@@ -15,9 +15,11 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use arrow_schema::{DataType, Field, Schema};
 use datafusion::prelude::{CsvReadOptions, SessionContext};
 use datafusion_common::{DFSchemaRef, Result, ToDFSchema};
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 use datafusion_expr::Expr;
 use datafusion_sql::unparser::Unparser;
 
@@ -27,10 +29,10 @@ use datafusion_sql::unparser::Unparser;
 /// b: Int32
 /// s: Float32
 fn schema() -> DFSchemaRef {
-    Schema::new(vec![
-        Field::new("a", DataType::Int32, true),
-        Field::new("b", DataType::Int32, false),
-        Field::new("c", DataType::Float32, false),
+    LogicalSchema::new(vec![
+        LogicalField::new("a", LogicalType::Int32, true),
+        LogicalField::new("b", LogicalType::Int32, false),
+        LogicalField::new("c", LogicalType::Float32, false),
     ])
     .to_dfschema_ref()
     .unwrap()
diff --git a/datafusion/core/tests/expr_api/simplification.rs b/datafusion/core/tests/expr_api/simplification.rs
index 9ce47153ba4a..38e1e8cd1551 100644
--- a/datafusion/core/tests/expr_api/simplification.rs
+++ b/datafusion/core/tests/expr_api/simplification.rs
@@ -37,6 +37,9 @@ use datafusion_optimizer::optimizer::Optimizer;
 use datafusion_optimizer::simplify_expressions::{ExprSimplifier, SimplifyExpressions};
 use datafusion_optimizer::{OptimizerContext, OptimizerRule};
 use std::sync::Arc;
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 /// In order to simplify expressions, DataFusion must have information
 /// about the expressions.
@@ -56,7 +59,7 @@ impl SimplifyInfo for MyInfo {
     fn is_boolean_type(&self, expr: &Expr) -> Result<bool> {
         Ok(matches!(
             expr.get_type(self.schema.as_ref())?,
-            DataType::Boolean
+            LogicalType::Boolean
         ))
     }
 
@@ -68,7 +71,7 @@ impl SimplifyInfo for MyInfo {
         &self.execution_props
     }
 
-    fn get_data_type(&self, expr: &Expr) -> Result<DataType> {
+    fn get_data_type(&self, expr: &Expr) -> Result<LogicalType> {
         expr.get_type(self.schema.as_ref())
     }
 }
@@ -88,10 +91,10 @@ impl From<DFSchemaRef> for MyInfo {
 /// b: Int32
 /// s: Utf8
 fn schema() -> DFSchemaRef {
-    Schema::new(vec![
-        Field::new("a", DataType::Int32, true),
-        Field::new("b", DataType::Int32, false),
-        Field::new("s", DataType::Utf8, false),
+    LogicalSchema::new(vec![
+        LogicalField::new("a", LogicalType::Int32, true),
+        LogicalField::new("b", LogicalType::Int32, false),
+        LogicalField::new("s", LogicalType::Utf8, false),
     ])
     .to_dfschema_ref()
     .unwrap()
@@ -190,7 +193,7 @@ fn make_udf_add(volatility: Volatility) -> Arc<ScalarUDF> {
 }
 
 fn cast_to_int64_expr(expr: Expr) -> Expr {
-    Expr::Cast(Cast::new(expr.into(), DataType::Int64))
+    Expr::Cast(Cast::new(expr.into(), LogicalType::Int64))
 }
 
 fn to_timestamp_expr(arg: impl Into<String>) -> Expr {
@@ -281,7 +284,7 @@ fn select_date_plus_interval() -> Result<()> {
     let schema = table_scan.schema();
 
     let date_plus_interval_expr = to_timestamp_expr(ts_string)
-        .cast_to(&DataType::Date32, schema)?
+        .cast_to(&LogicalType::Date32, schema)?
         + Expr::Literal(ScalarValue::IntervalDayTime(Some(IntervalDayTime {
             days: 123,
             milliseconds: 0,
@@ -483,15 +486,15 @@ fn multiple_now() -> Result<()> {
 // ------------------------------
 
 fn expr_test_schema() -> DFSchemaRef {
-    Schema::new(vec![
-        Field::new("c1", DataType::Utf8, true),
-        Field::new("c2", DataType::Boolean, true),
-        Field::new("c3", DataType::Int64, true),
-        Field::new("c4", DataType::UInt32, true),
-        Field::new("c1_non_null", DataType::Utf8, false),
-        Field::new("c2_non_null", DataType::Boolean, false),
-        Field::new("c3_non_null", DataType::Int64, false),
-        Field::new("c4_non_null", DataType::UInt32, false),
+    LogicalSchema::new(vec![
+        LogicalField::new("c1", LogicalType::Utf8, true),
+        LogicalField::new("c2", LogicalType::Boolean, true),
+        LogicalField::new("c3", LogicalType::Int64, true),
+        LogicalField::new("c4", LogicalType::UInt32, true),
+        LogicalField::new("c1_non_null", LogicalType::Utf8, false),
+        LogicalField::new("c2_non_null", LogicalType::Boolean, false),
+        LogicalField::new("c3_non_null", LogicalType::Int64, false),
+        LogicalField::new("c4_non_null", LogicalType::UInt32, false),
     ])
     .to_dfschema_ref()
     .unwrap()
@@ -688,8 +691,8 @@ fn test_simplify_concat() {
 #[test]
 fn test_simplify_cycles() {
     // cast(now() as int64) < cast(to_timestamp(0) as int64) + i64::MAX
-    let expr = cast(now(), DataType::Int64)
-        .lt(cast(to_timestamp(vec![lit(0)]), DataType::Int64) + lit(i64::MAX));
+    let expr = cast(now(), LogicalType::Int64)
+        .lt(cast(to_timestamp(vec![lit(0)]), LogicalType::Int64) + lit(i64::MAX));
     let expected = lit(true);
     test_simplify_with_cycle_count(expr, expected, 3);
 }
diff --git a/datafusion/core/tests/optimizer_integration.rs b/datafusion/core/tests/optimizer_integration.rs
index 39f745cd3309..40c91c4bd4ff 100644
--- a/datafusion/core/tests/optimizer_integration.rs
+++ b/datafusion/core/tests/optimizer_integration.rs
@@ -25,6 +25,8 @@ use std::sync::Arc;
 use arrow::datatypes::{DataType, Field, Schema, SchemaRef, TimeUnit};
 use arrow_schema::{Fields, SchemaBuilder};
 use datafusion_common::config::ConfigOptions;
+use datafusion_common::logical_type::schema::LogicalSchemaRef;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_common::tree_node::{TransformedResult, TreeNode};
 use datafusion_common::{plan_err, DFSchema, Result, ScalarValue};
 use datafusion_expr::interval_arithmetic::{Interval, NullableInterval};
@@ -203,7 +205,7 @@ impl ContextProvider for MyContextProvider {
         None
     }
 
-    fn get_variable_type(&self, _variable_names: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, _variable_names: &[String]) -> Option<LogicalType> {
         None
     }
 
@@ -259,7 +261,7 @@ fn test_nested_schema_nullability() {
 
     let dfschema = DFSchema::from_field_specific_qualified_schema(
         vec![Some("table_name".into()), None],
-        &Arc::new(schema),
+        &LogicalSchemaRef::new(schema.into()),
     )
     .unwrap();
 
diff --git a/datafusion/core/tests/parquet/page_pruning.rs b/datafusion/core/tests/parquet/page_pruning.rs
index 15efd4bcd9dd..cfe74b12e25a 100644
--- a/datafusion/core/tests/parquet/page_pruning.rs
+++ b/datafusion/core/tests/parquet/page_pruning.rs
@@ -35,6 +35,7 @@ use datafusion_physical_expr::create_physical_expr;
 use futures::StreamExt;
 use object_store::path::Path;
 use object_store::ObjectMeta;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 async fn get_parquet_exec(state: &SessionState, filter: Expr) -> ParquetExec {
     let object_store_url = ObjectStoreUrl::local_filesystem();
@@ -66,7 +67,7 @@ async fn get_parquet_exec(state: &SessionState, filter: Expr) -> ParquetExec {
         extensions: None,
     };
 
-    let df_schema = schema.clone().to_dfschema().unwrap();
+    let df_schema = LogicalSchema::from(schema.as_ref().clone()).to_dfschema().unwrap();
     let execution_props = ExecutionProps::new();
     let predicate = create_physical_expr(&filter, &df_schema, &execution_props).unwrap();
 
diff --git a/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs b/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs
index 5e3c44c039ab..2603290442b6 100644
--- a/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs
+++ b/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs
@@ -39,6 +39,8 @@ use datafusion_expr::{
 use datafusion_functions_array::range::range_udf;
 use parking_lot::Mutex;
 use sqlparser::ast::Ident;
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 
 /// test that casting happens on udfs.
 /// c11 is f32, but `custom_sqrt` requires f64. Casting happens but the logical plan and
@@ -518,14 +520,14 @@ impl ScalarUDFImpl for CastToI64UDF {
         // SimplifyInfo so we have to replicate some of the casting logic here.
 
         let source_type = info.get_data_type(&arg)?;
-        let new_expr = if source_type == DataType::Int64 {
+        let new_expr = if source_type == LogicalType::Int64 {
             // the argument's data type is already the correct type
             arg
         } else {
             // need to use an actual cast to get the correct type
             Expr::Cast(datafusion_expr::Cast {
                 expr: Box::new(arg),
-                data_type: DataType::Int64,
+                data_type: LogicalType::Int64,
             })
         };
         // return the newly written argument to DataFusion
@@ -645,7 +647,7 @@ impl ScalarUDFImpl for TakeUDF {
             );
         };
 
-        arg_exprs.get(take_idx).unwrap().get_type(schema)
+        arg_exprs.get(take_idx).unwrap().get_type(schema).map(|t| t.physical_type())
     }
 
     // The actual implementation
@@ -687,8 +689,8 @@ async fn verify_udf_return_type() -> Result<()> {
     // The output schema should be
     // * type of column smallint_col (int32)
     // * type of column double_col (float64)
-    assert_eq!(schema.field(0).data_type(), &DataType::Int32);
-    assert_eq!(schema.field(1).data_type(), &DataType::Float64);
+    assert_eq!(schema.field(0).data_type(), &LogicalType::Int32);
+    assert_eq!(schema.field(1).data_type(), &LogicalType::Float64);
 
     let expected = [
         "+-------+-------+",
@@ -835,13 +837,16 @@ impl TryFrom<CreateFunction> for ScalarFunctionWrapper {
                 .expect("Expression has to be defined!"),
             return_type: definition
                 .return_type
-                .expect("Return type has to be defined!"),
+                .expect("Return type has to be defined!")
+                .physical_type(),
+            // TODO(@notfilippo): avoid conversion to physical type
             signature: Signature::exact(
                 definition
                     .args
                     .unwrap_or_default()
                     .into_iter()
-                    .map(|a| a.data_type)
+                    // TODO(@notfilippo): avoid conversion to physical type
+                    .map(|a| a.data_type.physical_type())
                     .collect(),
                 definition
                     .params
@@ -990,10 +995,10 @@ async fn create_scalar_function_from_sql_statement_postgres_syntax() -> Result<(
                 value: "name".into(),
                 quote_style: None,
             }),
-            data_type: DataType::Utf8,
+            data_type: LogicalType::Utf8,
             default_expr: None,
         }]),
-        return_type: Some(DataType::Int32),
+        return_type: Some(LogicalType::Int32),
         params: CreateFunctionBody {
             language: Some(Ident {
                 value: "plrust".into(),
diff --git a/datafusion/expr/src/conditional_expressions.rs b/datafusion/expr/src/conditional_expressions.rs
index 7a2bf4b6c44a..176a2002501a 100644
--- a/datafusion/expr/src/conditional_expressions.rs
+++ b/datafusion/expr/src/conditional_expressions.rs
@@ -18,9 +18,9 @@
 //! Conditional expressions
 use crate::expr::Case;
 use crate::{expr_schema::ExprSchemable, Expr};
-use arrow::datatypes::DataType;
 use datafusion_common::{plan_err, DFSchema, Result};
 use std::collections::HashSet;
+use datafusion_common::logical_type::LogicalType;
 
 /// Helper struct for building [Expr::Case]
 pub struct CaseBuilder {
@@ -70,18 +70,18 @@ impl CaseBuilder {
             then_expr.push(e.as_ref().to_owned());
         }
 
-        let then_types: Vec<DataType> = then_expr
+        let then_types: Vec<LogicalType> = then_expr
             .iter()
             .map(|e| match e {
                 Expr::Literal(_) => e.get_type(&DFSchema::empty()),
-                _ => Ok(DataType::Null),
+                _ => Ok(LogicalType::Null),
             })
             .collect::<Result<Vec<_>>>()?;
 
-        if then_types.contains(&DataType::Null) {
+        if then_types.contains(&LogicalType::Null) {
             // cannot verify types until execution type
         } else {
-            let unique_types: HashSet<&DataType> = then_types.iter().collect();
+            let unique_types: HashSet<&LogicalType> = then_types.iter().collect();
             if unique_types.len() != 1 {
                 return plan_err!(
                     "CASE expression 'then' values had multiple data types: {unique_types:?}"
diff --git a/datafusion/expr/src/expr.rs b/datafusion/expr/src/expr.rs
index 846b627b2242..0c084c8cadb7 100644
--- a/datafusion/expr/src/expr.rs
+++ b/datafusion/expr/src/expr.rs
@@ -33,7 +33,7 @@ use crate::{
 };
 use crate::{window_frame, Volatility};
 
-use arrow::datatypes::{DataType, FieldRef};
+use arrow::datatypes::DataType;
 use datafusion_common::tree_node::{
     Transformed, TransformedResult, TreeNode, TreeNodeRecursion,
 };
@@ -41,6 +41,8 @@ use datafusion_common::{
     internal_err, plan_err, Column, DFSchema, Result, ScalarValue, TableReference,
 };
 use sqlparser::ast::NullTreatment;
+use datafusion_common::logical_type::field::LogicalFieldRef;
+use datafusion_common::logical_type::LogicalType;
 
 /// Represents logical expressions such as `A + 1`, or `CAST(c1 AS int)`.
 ///
@@ -153,7 +155,7 @@ use sqlparser::ast::NullTreatment;
 ///    Field::new("c2", DataType::Float64, false),
 /// ]);
 /// // DFSchema is a an Arrow schema with optional relation name
-/// let df_schema = DFSchema::try_from_qualified_schema("t1", &arrow_schema)
+/// let df_schema = DFSchema::try_from_qualified_schema("t1", &arrow_schema.into())
 ///   .unwrap();
 ///
 /// // Form Vec<Expr> with an expression for each column in the schema
@@ -223,7 +225,7 @@ pub enum Expr {
     /// A named reference to a qualified filed in a schema.
     Column(Column),
     /// A named reference to a variable in a registry.
-    ScalarVariable(DataType, Vec<String>),
+    ScalarVariable(LogicalType, Vec<String>),
     /// A constant value.
     Literal(ScalarValue),
     /// A binary expression such as "age > 21"
@@ -317,7 +319,7 @@ pub enum Expr {
     Placeholder(Placeholder),
     /// A place holder which hold a reference to a qualified field
     /// in the outer query, used for correlated sub queries.
-    OuterReferenceColumn(DataType, Column),
+    OuterReferenceColumn(LogicalType, Column),
     /// Unnest expression
     Unnest(Unnest),
 }
@@ -339,8 +341,8 @@ impl From<Column> for Expr {
 /// useful for creating [`Expr`] from a [`DFSchema`].
 ///
 /// See example on [`Expr`]
-impl<'a> From<(Option<&'a TableReference>, &'a FieldRef)> for Expr {
-    fn from(value: (Option<&'a TableReference>, &'a FieldRef)) -> Self {
+impl<'a> From<(Option<&'a TableReference>, &'a LogicalFieldRef)> for Expr {
+    fn from(value: (Option<&'a TableReference>, &'a LogicalFieldRef)) -> Self {
         Expr::from(Column::from(value))
     }
 }
@@ -558,13 +560,13 @@ pub enum GetFieldAccess {
 pub struct Cast {
     /// The expression being cast
     pub expr: Box<Expr>,
-    /// The `DataType` the expression will yield
-    pub data_type: DataType,
+    /// The `LogicalType` the expression will yield
+    pub data_type: LogicalType,
 }
 
 impl Cast {
     /// Create a new Cast expression
-    pub fn new(expr: Box<Expr>, data_type: DataType) -> Self {
+    pub fn new(expr: Box<Expr>, data_type: LogicalType) -> Self {
         Self { expr, data_type }
     }
 }
@@ -574,13 +576,13 @@ impl Cast {
 pub struct TryCast {
     /// The expression being cast
     pub expr: Box<Expr>,
-    /// The `DataType` the expression will yield
-    pub data_type: DataType,
+    /// The `LogicalType` the expression will yield
+    pub data_type: LogicalType,
 }
 
 impl TryCast {
     /// Create a new TryCast expression
-    pub fn new(expr: Box<Expr>, data_type: DataType) -> Self {
+    pub fn new(expr: Box<Expr>, data_type: LogicalType) -> Self {
         Self { expr, data_type }
     }
 }
@@ -926,12 +928,12 @@ pub struct Placeholder {
     /// The identifier of the parameter, including the leading `$` (e.g, `"$1"` or `"$foo"`)
     pub id: String,
     /// The type the parameter will be filled in with
-    pub data_type: Option<DataType>,
+    pub data_type: Option<LogicalType>,
 }
 
 impl Placeholder {
     /// Create a new Placeholder expression
-    pub fn new(id: String, data_type: Option<DataType>) -> Self {
+    pub fn new(id: String, data_type: Option<LogicalType>) -> Self {
         Self { id, data_type }
     }
 }
@@ -2060,7 +2062,7 @@ fn write_name<W: Write>(w: &mut W, e: &Expr) -> Result<()> {
         Expr::InSubquery(InSubquery { negated: true, .. }) => w.write_str("NOT IN")?,
         Expr::InSubquery(InSubquery { negated: false, .. }) => w.write_str("IN")?,
         Expr::ScalarSubquery(subquery) => {
-            w.write_str(subquery.subquery.schema().field(0).name().as_str())?;
+            w.write_str(subquery.subquery.schema().field(0).name())?;
         }
         Expr::Unnest(Unnest { expr }) => {
             w.write_str("unnest(")?;
@@ -2222,7 +2224,7 @@ mod test {
     fn format_cast() -> Result<()> {
         let expr = Expr::Cast(Cast {
             expr: Box::new(Expr::Literal(ScalarValue::Float32(Some(1.23)))),
-            data_type: DataType::Utf8,
+            data_type: LogicalType::Utf8,
         });
         let expected_canonical = "CAST(Float32(1.23) AS Utf8)";
         assert_eq!(expected_canonical, expr.canonical_name());
@@ -2255,7 +2257,7 @@ mod test {
     fn test_collect_expr() -> Result<()> {
         // single column
         {
-            let expr = &Expr::Cast(Cast::new(Box::new(col("a")), DataType::Float64));
+            let expr = &Expr::Cast(Cast::new(Box::new(col("a")), LogicalType::Float64));
             let columns = expr.column_refs();
             assert_eq!(1, columns.len());
             assert!(columns.contains(&Column::from_name("a")));
diff --git a/datafusion/expr/src/expr_fn.rs b/datafusion/expr/src/expr_fn.rs
index 8b0213fd52fd..2db73e5c413b 100644
--- a/datafusion/expr/src/expr_fn.rs
+++ b/datafusion/expr/src/expr_fn.rs
@@ -40,6 +40,7 @@ use std::any::Any;
 use std::fmt::Debug;
 use std::ops::Not;
 use std::sync::Arc;
+use datafusion_common::logical_type::LogicalType;
 
 /// Create a column expression based on a qualified or unqualified column name. Will
 /// normalize unquoted identifiers according to SQL rules (identifiers will become lowercase).
@@ -62,7 +63,7 @@ pub fn col(ident: impl Into<Column>) -> Expr {
 
 /// Create an out reference column which hold a reference that has been resolved to a field
 /// outside of the current plan.
-pub fn out_ref_col(dt: DataType, ident: impl Into<Column>) -> Expr {
+pub fn out_ref_col(dt: LogicalType, ident: impl Into<Column>) -> Expr {
     Expr::OuterReferenceColumn(dt, ident.into())
 }
 
@@ -308,12 +309,12 @@ pub fn rollup(exprs: Vec<Expr>) -> Expr {
 }
 
 /// Create a cast expression
-pub fn cast(expr: Expr, data_type: DataType) -> Expr {
+pub fn cast(expr: Expr, data_type: LogicalType) -> Expr {
     Expr::Cast(Cast::new(Box::new(expr), data_type))
 }
 
 /// Create a try cast expression
-pub fn try_cast(expr: Expr, data_type: DataType) -> Expr {
+pub fn try_cast(expr: Expr, data_type: LogicalType) -> Expr {
     Expr::TryCast(TryCast::new(Box::new(expr), data_type))
 }
 
diff --git a/datafusion/expr/src/expr_rewriter/mod.rs b/datafusion/expr/src/expr_rewriter/mod.rs
index 1441374bdba3..ea3d6f353aa9 100644
--- a/datafusion/expr/src/expr_rewriter/mod.rs
+++ b/datafusion/expr/src/expr_rewriter/mod.rs
@@ -286,7 +286,9 @@ mod test {
     use super::*;
     use crate::expr::Sort;
     use crate::{col, lit, Cast};
-    use arrow::datatypes::{DataType, Field, Schema};
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
+    use datafusion_common::logical_type::schema::LogicalSchema;
     use datafusion_common::ScalarValue;
 
     #[derive(Default)]
@@ -407,10 +409,10 @@ mod test {
     ) -> DFSchema {
         let fields = fields
             .iter()
-            .map(|f| Arc::new(Field::new(f.to_string(), DataType::Int8, false)))
+            .map(|f| Arc::new(LogicalField::new(f.to_string(), LogicalType::Int8, false)))
             .collect::<Vec<_>>();
-        let schema = Arc::new(Schema::new(fields));
-        DFSchema::from_field_specific_qualified_schema(qualifiers, &schema).unwrap()
+        let schema = Arc::new(LogicalSchema::new(fields));
+        DFSchema::from_field_specific_qualified_schema(qualifiers, &schema.into()).unwrap()
     }
 
     #[test]
@@ -440,7 +442,7 @@ mod test {
         // cast data types
         test_rewrite(
             col("a"),
-            Expr::Cast(Cast::new(Box::new(col("a")), DataType::Int32)),
+            Expr::Cast(Cast::new(Box::new(col("a")), LogicalType::Int32)),
         );
 
         // change literal type from i32 to i64
diff --git a/datafusion/expr/src/expr_rewriter/order_by.rs b/datafusion/expr/src/expr_rewriter/order_by.rs
index 4b56ca3d1c2e..8084995bdf63 100644
--- a/datafusion/expr/src/expr_rewriter/order_by.rs
+++ b/datafusion/expr/src/expr_rewriter/order_by.rs
@@ -154,7 +154,7 @@ mod test {
     use std::sync::Arc;
 
     use arrow::datatypes::{DataType, Field, Schema};
-
+    use datafusion_common::logical_type::LogicalType;
     use crate::{
         cast, col, lit, logical_plan::builder::LogicalTableSource, min,
         test::function_stub::avg, try_cast, LogicalPlanBuilder,
@@ -270,13 +270,13 @@ mod test {
         let cases = vec![
             TestCase {
                 desc: "Cast is preserved by rewrite_sort_cols_by_aggs",
-                input: sort(cast(col("c2"), DataType::Int64)),
-                expected: sort(cast(col("c2").alias("c2"), DataType::Int64)),
+                input: sort(cast(col("c2"), LogicalType::Int64)),
+                expected: sort(cast(col("c2").alias("c2"), LogicalType::Int64)),
             },
             TestCase {
                 desc: "TryCast is preserved by rewrite_sort_cols_by_aggs",
-                input: sort(try_cast(col("c2"), DataType::Int64)),
-                expected: sort(try_cast(col("c2").alias("c2"), DataType::Int64)),
+                input: sort(try_cast(col("c2"), LogicalType::Int64)),
+                expected: sort(try_cast(col("c2").alias("c2"), LogicalType::Int64)),
             },
         ];
 
diff --git a/datafusion/expr/src/expr_schema.rs b/datafusion/expr/src/expr_schema.rs
index d5a04ad4ae1f..8106be838676 100644
--- a/datafusion/expr/src/expr_schema.rs
+++ b/datafusion/expr/src/expr_schema.rs
@@ -26,18 +26,20 @@ use crate::type_coercion::functions::{
 };
 use crate::{utils, LogicalPlan, Projection, Subquery, WindowFunctionDefinition};
 use arrow::compute::can_cast_types;
-use arrow::datatypes::{DataType, Field};
 use datafusion_common::{
     internal_err, not_impl_err, plan_datafusion_err, plan_err, Column, ExprSchema,
     Result, TableReference,
 };
 use std::collections::HashMap;
 use std::sync::Arc;
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
 
 /// trait to allow expr to typable with respect to a schema
 pub trait ExprSchemable {
     /// given a schema, return the type of the expr
-    fn get_type(&self, schema: &dyn ExprSchema) -> Result<DataType>;
+    fn get_type(&self, schema: &dyn ExprSchema) -> Result<LogicalType>;
 
     /// given a schema, return the nullability of the expr
     fn nullable(&self, input_schema: &dyn ExprSchema) -> Result<bool>;
@@ -49,14 +51,14 @@ pub trait ExprSchemable {
     fn to_field(
         &self,
         input_schema: &dyn ExprSchema,
-    ) -> Result<(Option<TableReference>, Arc<Field>)>;
+    ) -> Result<(Option<TableReference>, Arc<LogicalField>)>;
 
     /// cast to a type with respect to a schema
-    fn cast_to(self, cast_to_type: &DataType, schema: &dyn ExprSchema) -> Result<Expr>;
+    fn cast_to(self, cast_to_type: &LogicalType, schema: &dyn ExprSchema) -> Result<Expr>;
 
     /// given a schema, return the type and nullability of the expr
     fn data_type_and_nullable(&self, schema: &dyn ExprSchema)
-        -> Result<(DataType, bool)>;
+        -> Result<(LogicalType, bool)>;
 }
 
 impl ExprSchemable for Expr {
@@ -98,7 +100,7 @@ impl ExprSchemable for Expr {
     /// expression refers to a column that does not exist in the
     /// schema, or when the expression is incorrectly typed
     /// (e.g. `[utf8] + [bool]`).
-    fn get_type(&self, schema: &dyn ExprSchema) -> Result<DataType> {
+    fn get_type(&self, schema: &dyn ExprSchema) -> Result<LogicalType> {
         match self {
             Expr::Alias(Alias { expr, name, .. }) => match &**expr {
                 Expr::Placeholder(Placeholder { data_type, .. }) => match &data_type {
@@ -111,7 +113,7 @@ impl ExprSchemable for Expr {
             Expr::Column(c) => Ok(schema.data_type(c)?.clone()),
             Expr::OuterReferenceColumn(ty, _) => Ok(ty.clone()),
             Expr::ScalarVariable(ty, _) => Ok(ty.clone()),
-            Expr::Literal(l) => Ok(l.data_type()),
+            Expr::Literal(l) => Ok(l.data_type().into()),
             Expr::Case(case) => case.when_then_expr[0].1.get_type(schema),
             Expr::Cast(Cast { data_type, .. })
             | Expr::TryCast(TryCast { data_type, .. }) => Ok(data_type.clone()),
@@ -119,13 +121,13 @@ impl ExprSchemable for Expr {
                 let arg_data_type = expr.get_type(schema)?;
                 // Unnest's output type is the inner type of the list
                 match arg_data_type{
-                    DataType::List(field) | DataType::LargeList(field) | DataType::FixedSizeList(field, _) =>{
+                    LogicalType::List(field) | LogicalType::LargeList(field) | LogicalType::FixedSizeList(field, _) =>{
                         Ok(field.data_type().clone())
                     }
-                    DataType::Struct(_) => {
+                    LogicalType::Struct(_) => {
                         Ok(arg_data_type)
                     }
-                    DataType::Null => {
+                    LogicalType::Null => {
                         not_impl_err!("unnest() does not support null yet")
                     }
                     _ => {
@@ -138,28 +140,40 @@ impl ExprSchemable for Expr {
                     .iter()
                     .map(|e| e.get_type(schema))
                     .collect::<Result<Vec<_>>>()?;
-                        // verify that function is invoked with correct number and type of arguments as defined in `TypeSignature`
-                        data_types_with_scalar_udf(&arg_data_types, func).map_err(|err| {
-                            plan_datafusion_err!(
-                                "{} {}",
-                                err,
-                                utils::generate_signature_error_msg(
-                                    func.name(),
-                                    func.signature().clone(),
-                                    &arg_data_types,
-                                )
-                            )
-                        })?;
 
-                        // perform additional function arguments validation (due to limited
-                        // expressiveness of `TypeSignature`), then infer return type
-                        Ok(func.return_type_from_exprs(args, schema, &arg_data_types)?)
+                // TODO(@notfilippo): not convert to DataType
+                let arg_data_types = arg_data_types
+                    .into_iter()
+                    .map(|e| e.physical_type())
+                    .collect::<Vec<_>>();
+
+                // verify that function is invoked with correct number and type of arguments as defined in `TypeSignature`
+                data_types_with_scalar_udf(&arg_data_types, func).map_err(|err| {
+                    plan_datafusion_err!(
+                        "{} {}",
+                        err,
+                        utils::generate_signature_error_msg(
+                            func.name(),
+                            func.signature().clone(),
+                            &arg_data_types,
+                        )
+                    )
+                })?;
+
+                // perform additional function arguments validation (due to limited
+                // expressiveness of `TypeSignature`), then infer return type
+                Ok(func.return_type_from_exprs(args, schema, &arg_data_types)?.into())
             }
             Expr::WindowFunction(WindowFunction { fun, args, .. }) => {
                 let data_types = args
                     .iter()
                     .map(|e| e.get_type(schema))
                     .collect::<Result<Vec<_>>>()?;
+                // TODO(@notfilippo): not convert to DataType
+                let data_types = data_types
+                    .into_iter()
+                    .map(|e| e.physical_type())
+                    .collect::<Vec<_>>();
                 let nullability = args
                     .iter()
                     .map(|e| e.nullable(schema))
@@ -177,10 +191,10 @@ impl ExprSchemable for Expr {
                                 )
                             )
                         })?;
-                        Ok(fun.return_type(&new_types, &nullability)?)
+                        Ok(fun.return_type(&new_types, &nullability)?.into())
                     }
                     _ => {
-                        fun.return_type(&data_types, &nullability)
+                        Ok(fun.return_type(&data_types, &nullability)?.into())
                     }
                 }
             }
@@ -193,9 +207,14 @@ impl ExprSchemable for Expr {
                     .iter()
                     .map(|e| e.nullable(schema))
                     .collect::<Result<Vec<_>>>()?;
+                // TODO(@notfilippo): not convert to DataType
+                let data_types = data_types
+                    .into_iter()
+                    .map(|e| e.physical_type())
+                    .collect::<Vec<_>>();
                 match func_def {
                     AggregateFunctionDefinition::BuiltIn(fun) => {
-                        fun.return_type(&data_types, &nullability)
+                        Ok(fun.return_type(&data_types, &nullability)?.into())
                     }
                     AggregateFunctionDefinition::UDF(fun) => {
                         let new_types = data_types_with_aggregate_udf(&data_types, fun).map_err(|err| {
@@ -209,7 +228,7 @@ impl ExprSchemable for Expr {
                                 )
                             )
                         })?;
-                        Ok(fun.return_type(&new_types)?)
+                        Ok(fun.return_type(&new_types)?.into())
                     }
                 }
             }
@@ -225,7 +244,7 @@ impl ExprSchemable for Expr {
             | Expr::IsUnknown(_)
             | Expr::IsNotTrue(_)
             | Expr::IsNotFalse(_)
-            | Expr::IsNotUnknown(_) => Ok(DataType::Boolean),
+            | Expr::IsNotUnknown(_) => Ok(LogicalType::Boolean),
             Expr::ScalarSubquery(subquery) => {
                 Ok(subquery.subquery.schema().field(0).data_type().clone())
             }
@@ -233,8 +252,9 @@ impl ExprSchemable for Expr {
                 ref left,
                 ref right,
                 ref op,
-            }) => get_result_type(&left.get_type(schema)?, op, &right.get_type(schema)?),
-            Expr::Like { .. } | Expr::SimilarTo { .. } => Ok(DataType::Boolean),
+                // TODO(@notfilippo): do not convert to physical type
+            }) => Ok(get_result_type(&left.get_type(schema)?.physical_type(), op, &right.get_type(schema)?.physical_type())?.into()),
+            Expr::Like { .. } | Expr::SimilarTo { .. } => Ok(LogicalType::Boolean),
             Expr::Placeholder(Placeholder { data_type, .. }) => {
                 data_type.clone().ok_or_else(|| {
                     plan_datafusion_err!("Placeholder type could not be resolved. Make sure that the placeholder is bound to a concrete type, e.g. by providing parameter values.")
@@ -244,12 +264,12 @@ impl ExprSchemable for Expr {
                 // Wildcard do not really have a type and do not appear in projections
                 match qualifier {
                     Some(_) => internal_err!("QualifiedWildcard expressions are not valid in a logical query plan"),
-                    None => Ok(DataType::Null)
+                    None => Ok(LogicalType::Null)
                 }
             }
             Expr::GroupingSet(_) => {
                 // grouping sets do not really have a type and do not appear in projections
-                Ok(DataType::Null)
+                Ok(LogicalType::Null)
             }
         }
     }
@@ -392,7 +412,7 @@ impl ExprSchemable for Expr {
     fn data_type_and_nullable(
         &self,
         schema: &dyn ExprSchema,
-    ) -> Result<(DataType, bool)> {
+    ) -> Result<(LogicalType, bool)> {
         match self {
             Expr::Alias(Alias { expr, name, .. }) => match &**expr {
                 Expr::Placeholder(Placeholder { data_type, .. }) => match &data_type {
@@ -411,7 +431,7 @@ impl ExprSchemable for Expr {
                 .map(|(d, n)| (d.clone(), n)),
             Expr::OuterReferenceColumn(ty, _) => Ok((ty.clone(), true)),
             Expr::ScalarVariable(ty, _) => Ok((ty.clone(), true)),
-            Expr::Literal(l) => Ok((l.data_type(), l.is_null())),
+            Expr::Literal(l) => Ok((l.data_type().into(), l.is_null())),
             Expr::IsNull(_)
             | Expr::IsNotNull(_)
             | Expr::IsTrue(_)
@@ -420,7 +440,7 @@ impl ExprSchemable for Expr {
             | Expr::IsNotTrue(_)
             | Expr::IsNotFalse(_)
             | Expr::IsNotUnknown(_)
-            | Expr::Exists { .. } => Ok((DataType::Boolean, false)),
+            | Expr::Exists { .. } => Ok((LogicalType::Boolean, false)),
             Expr::ScalarSubquery(subquery) => Ok((
                 subquery.subquery.schema().field(0).data_type().clone(),
                 subquery.subquery.schema().field(0).is_nullable(),
@@ -432,7 +452,8 @@ impl ExprSchemable for Expr {
             }) => {
                 let left = left.data_type_and_nullable(schema)?;
                 let right = right.data_type_and_nullable(schema)?;
-                Ok((get_result_type(&left.0, op, &right.0)?, left.1 || right.1))
+                // TODO(@notfilippo): do not convert to physical type
+                Ok((get_result_type(&left.0.physical_type(), op, &right.0.physical_type())?.into(), left.1 || right.1))
             }
             _ => Ok((self.get_type(schema)?, self.nullable(schema)?)),
         }
@@ -445,13 +466,13 @@ impl ExprSchemable for Expr {
     fn to_field(
         &self,
         input_schema: &dyn ExprSchema,
-    ) -> Result<(Option<TableReference>, Arc<Field>)> {
+    ) -> Result<(Option<TableReference>, Arc<LogicalField>)> {
         match self {
             Expr::Column(c) => {
                 let (data_type, nullable) = self.data_type_and_nullable(input_schema)?;
                 Ok((
                     c.relation.clone(),
-                    Field::new(&c.name, data_type, nullable)
+                    LogicalField::new(&c.name, data_type, nullable)
                         .with_metadata(self.metadata(input_schema)?)
                         .into(),
                 ))
@@ -460,7 +481,7 @@ impl ExprSchemable for Expr {
                 let (data_type, nullable) = self.data_type_and_nullable(input_schema)?;
                 Ok((
                     relation.clone(),
-                    Field::new(name, data_type, nullable)
+                    LogicalField::new(name, data_type, nullable)
                         .with_metadata(self.metadata(input_schema)?)
                         .into(),
                 ))
@@ -469,7 +490,7 @@ impl ExprSchemable for Expr {
                 let (data_type, nullable) = self.data_type_and_nullable(input_schema)?;
                 Ok((
                     None,
-                    Field::new(self.display_name()?, data_type, nullable)
+                    LogicalField::new(self.display_name()?, data_type, nullable)
                         .with_metadata(self.metadata(input_schema)?)
                         .into(),
                 ))
@@ -483,7 +504,7 @@ impl ExprSchemable for Expr {
     ///
     /// This function errors when it is impossible to cast the
     /// expression to the target [arrow::datatypes::DataType].
-    fn cast_to(self, cast_to_type: &DataType, schema: &dyn ExprSchema) -> Result<Expr> {
+    fn cast_to(self, cast_to_type: &LogicalType, schema: &dyn ExprSchema) -> Result<Expr> {
         let this_type = self.get_type(schema)?;
         if this_type == *cast_to_type {
             return Ok(self);
@@ -493,7 +514,8 @@ impl ExprSchemable for Expr {
         // like all of the binary expressions below. Perhaps Expr should track the
         // type of the expression?
 
-        if can_cast_types(&this_type, cast_to_type) {
+        // TODO(@notfilippo): The basis for whether cast can be executed should be the logical type
+        if can_cast_types(&this_type.physical_type(), &cast_to_type.physical_type()) {
             match self {
                 Expr::ScalarSubquery(subquery) => {
                     Ok(Expr::ScalarSubquery(cast_subquery(subquery, cast_to_type)?))
@@ -507,7 +529,7 @@ impl ExprSchemable for Expr {
 }
 
 /// cast subquery in InSubquery/ScalarSubquery to a given type.
-pub fn cast_subquery(subquery: Subquery, cast_to_type: &DataType) -> Result<Subquery> {
+pub fn cast_subquery(subquery: Subquery, cast_to_type: &LogicalType) -> Result<Subquery> {
     if subquery.subquery.schema().field(0).data_type() == cast_to_type {
         return Ok(subquery);
     }
@@ -574,7 +596,7 @@ mod tests {
     fn test_between_nullability() {
         let get_schema = |nullable| {
             MockExprSchema::new()
-                .with_data_type(DataType::Int32)
+                .with_data_type(LogicalType::Int32)
                 .with_nullable(nullable)
         };
 
@@ -598,7 +620,7 @@ mod tests {
     fn test_inlist_nullability() {
         let get_schema = |nullable| {
             MockExprSchema::new()
-                .with_data_type(DataType::Int32)
+                .with_data_type(LogicalType::Int32)
                 .with_nullable(nullable)
         };
 
@@ -623,7 +645,7 @@ mod tests {
     fn test_like_nullability() {
         let get_schema = |nullable| {
             MockExprSchema::new()
-                .with_data_type(DataType::Utf8)
+                .with_data_type(LogicalType::Utf8)
                 .with_nullable(nullable)
         };
 
@@ -639,8 +661,8 @@ mod tests {
     fn expr_schema_data_type() {
         let expr = col("foo");
         assert_eq!(
-            DataType::Utf8,
-            expr.get_type(&MockExprSchema::new().with_data_type(DataType::Utf8))
+            LogicalType::Utf8,
+            expr.get_type(&MockExprSchema::new().with_data_type(LogicalType::Utf8))
                 .unwrap()
         );
     }
@@ -651,7 +673,7 @@ mod tests {
         meta.insert("bar".to_string(), "buzz".to_string());
         let expr = col("foo");
         let schema = MockExprSchema::new()
-            .with_data_type(DataType::Int32)
+            .with_data_type(LogicalType::Int32)
             .with_metadata(meta.clone());
 
         // col and alias should be metadata-preserving
@@ -662,14 +684,14 @@ mod tests {
         assert_eq!(
             HashMap::new(),
             expr.clone()
-                .cast_to(&DataType::Int64, &schema)
+                .cast_to(&LogicalType::Int64, &schema)
                 .unwrap()
                 .metadata(&schema)
                 .unwrap()
         );
 
         let schema = DFSchema::from_unqualifed_fields(
-            vec![Field::new("foo", DataType::Int32, true).with_metadata(meta.clone())]
+            vec![LogicalField::new("foo", LogicalType::Int32, true).with_metadata(meta.clone())]
                 .into(),
             HashMap::new(),
         )
@@ -682,7 +704,7 @@ mod tests {
     #[derive(Debug)]
     struct MockExprSchema {
         nullable: bool,
-        data_type: DataType,
+        data_type: LogicalType,
         error_on_nullable: bool,
         metadata: HashMap<String, String>,
     }
@@ -691,7 +713,7 @@ mod tests {
         fn new() -> Self {
             Self {
                 nullable: false,
-                data_type: DataType::Null,
+                data_type: LogicalType::Null,
                 error_on_nullable: false,
                 metadata: HashMap::new(),
             }
@@ -702,7 +724,7 @@ mod tests {
             self
         }
 
-        fn with_data_type(mut self, data_type: DataType) -> Self {
+        fn with_data_type(mut self, data_type: LogicalType) -> Self {
             self.data_type = data_type;
             self
         }
@@ -727,7 +749,7 @@ mod tests {
             }
         }
 
-        fn data_type(&self, _col: &Column) -> Result<&DataType> {
+        fn data_type(&self, _col: &Column) -> Result<&LogicalType> {
             Ok(&self.data_type)
         }
 
@@ -735,7 +757,7 @@ mod tests {
             Ok(&self.metadata)
         }
 
-        fn data_type_and_nullable(&self, col: &Column) -> Result<(&DataType, bool)> {
+        fn data_type_and_nullable(&self, col: &Column) -> Result<(&LogicalType, bool)> {
             Ok((self.data_type(col)?, self.nullable(col)?))
         }
     }
diff --git a/datafusion/expr/src/logical_plan/builder.rs b/datafusion/expr/src/logical_plan/builder.rs
index f87151efd88b..3b5be7a839d7 100644
--- a/datafusion/expr/src/logical_plan/builder.rs
+++ b/datafusion/expr/src/logical_plan/builder.rs
@@ -48,14 +48,15 @@ use crate::{
     WriteOp,
 };
 
-use arrow::datatypes::{DataType, Field, Fields, Schema, SchemaRef};
+use arrow::datatypes::{Schema, SchemaRef};
 use datafusion_common::display::ToStringifiedPlan;
 use datafusion_common::file_options::file_type::FileType;
-use datafusion_common::{
-    get_target_functional_dependencies, internal_err, not_impl_err, plan_datafusion_err,
-    plan_err, Column, DFSchema, DFSchemaRef, DataFusionError, Result, ScalarValue,
-    TableReference, ToDFSchema, UnnestOptions,
-};
+use datafusion_common::{get_target_functional_dependencies, internal_err, not_impl_err, plan_datafusion_err, plan_err, Column, DFSchema, DFSchemaRef, DataFusionError, Result, ScalarValue, TableReference, UnnestOptions, ToDFSchema};
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::fields::LogicalFields;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 /// Default table name for unnamed table
 pub const UNNAMED_TABLE: &str = "?table?";
@@ -182,26 +183,26 @@ impl LogicalPlanBuilder {
         }
 
         let empty_schema = DFSchema::empty();
-        let mut field_types: Vec<DataType> = Vec::with_capacity(n_cols);
+        let mut field_types: Vec<LogicalType> = Vec::with_capacity(n_cols);
         for j in 0..n_cols {
-            let mut common_type: Option<DataType> = None;
+            let mut common_type: Option<LogicalType> = None;
             for (i, row) in values.iter().enumerate() {
                 let value = &row[j];
                 let data_type = value.get_type(&empty_schema)?;
-                if data_type == DataType::Null {
+                if data_type == LogicalType::Null {
                     continue;
                 }
                 if let Some(prev_type) = common_type {
                     // get common type of each column values.
-                    let Some(new_type) = values_coercion(&data_type, &prev_type) else {
+                    let Some(new_type) = values_coercion(&data_type.physical_type(), &prev_type.physical_type()) else {
                         return plan_err!("Inconsistent data type across values list at row {i} column {j}. Was {prev_type} but found {data_type}");
                     };
-                    common_type = Some(new_type);
+                    common_type = Some(new_type.into());
                 } else {
                     common_type = Some(data_type.clone());
                 }
             }
-            field_types.push(common_type.unwrap_or(DataType::Utf8));
+            field_types.push(common_type.unwrap_or(LogicalType::Utf8));
         }
         // wrap cast if data type is not same as common type.
         for row in &mut values {
@@ -220,7 +221,7 @@ impl LogicalPlanBuilder {
             .map(|(j, data_type)| {
                 // naming is following convention https://www.postgresql.org/docs/current/queries-values.html
                 let name = &format!("column{}", j + 1);
-                Field::new(name, data_type.clone(), true)
+                LogicalField::new(name, data_type.clone(), true)
             })
             .collect::<Vec<_>>();
         let dfschema = DFSchema::from_unqualifed_fields(fields.into(), HashMap::new())?;
@@ -289,7 +290,7 @@ impl LogicalPlanBuilder {
     pub fn insert_into(
         input: LogicalPlan,
         table_name: impl Into<TableReference>,
-        table_schema: &Schema,
+        table_schema: &LogicalSchema,
         overwrite: bool,
     ) -> Result<Self> {
         let table_schema = table_schema.clone().to_dfschema_ref()?;
@@ -383,7 +384,7 @@ impl LogicalPlanBuilder {
     }
 
     /// Make a builder for a prepare logical plan from the builder's plan
-    pub fn prepare(self, name: String, data_types: Vec<DataType>) -> Result<Self> {
+    pub fn prepare(self, name: String, data_types: Vec<LogicalType>) -> Result<Self> {
         Ok(Self::from(LogicalPlan::Prepare(Prepare {
             name,
             data_types,
@@ -1181,7 +1182,7 @@ impl From<Arc<LogicalPlan>> for LogicalPlanBuilder {
     }
 }
 
-pub fn change_redundant_column(fields: &Fields) -> Vec<Field> {
+pub fn change_redundant_column(fields: &LogicalFields) -> Vec<LogicalField> {
     let mut name_map = HashMap::new();
     fields
         .into_iter()
@@ -1190,7 +1191,7 @@ pub fn change_redundant_column(fields: &Fields) -> Vec<Field> {
             *counter += 1;
             if *counter > 1 {
                 let new_name = format!("{}:{}", field.name(), *counter - 1);
-                Field::new(new_name, field.data_type().clone(), field.is_nullable())
+                LogicalField::new(new_name, field.data_type().clone(), field.is_nullable())
             } else {
                 field.as_ref().clone()
             }
@@ -1205,8 +1206,8 @@ pub fn build_join_schema(
     join_type: &JoinType,
 ) -> Result<DFSchema> {
     fn nullify_fields<'a>(
-        fields: impl Iterator<Item = (Option<&'a TableReference>, &'a Arc<Field>)>,
-    ) -> Vec<(Option<TableReference>, Arc<Field>)> {
+        fields: impl Iterator<Item = (Option<&'a TableReference>, &'a Arc<LogicalField>)>,
+    ) -> Vec<(Option<TableReference>, Arc<LogicalField>)> {
         fields
             .map(|(q, f)| {
                 // TODO: find a good way to do that
@@ -1219,7 +1220,7 @@ pub fn build_join_schema(
     let right_fields = right.iter();
     let left_fields = left.iter();
 
-    let qualified_fields: Vec<(Option<TableReference>, Arc<Field>)> = match join_type {
+    let qualified_fields: Vec<(Option<TableReference>, Arc<LogicalField>)> = match join_type {
         JoinType::Inner => {
             // left then right
             let left_fields = left_fields
@@ -1377,9 +1378,10 @@ pub fn union(left_plan: LogicalPlan, right_plan: LogicalPlan) -> Result<LogicalP
             .map(
                 |((left_qualifier, left_field), (_right_qualifier, right_field))| {
                     let nullable = left_field.is_nullable() || right_field.is_nullable();
+                    // TODO(@notfilippo): do not convert to physical type
                     let data_type = comparison_coercion(
-                        left_field.data_type(),
-                        right_field.data_type(),
+                        &left_field.data_type().physical_type(),
+                        &right_field.data_type().physical_type(),
                     )
                     .ok_or_else(|| {
                         plan_datafusion_err!(
@@ -1392,7 +1394,7 @@ pub fn union(left_plan: LogicalPlan, right_plan: LogicalPlan) -> Result<LogicalP
                     })?;
                     Ok((
                         left_qualifier.cloned(),
-                        Arc::new(Field::new(left_field.name(), data_type, nullable)),
+                        Arc::new(LogicalField::new(left_field.name(), data_type.into(), nullable)),
                     ))
                 },
             )
@@ -1602,15 +1604,15 @@ pub fn unnest(input: LogicalPlan, columns: Vec<Column>) -> Result<LogicalPlan> {
 // - Struct(field1, field2) returns ["a.field1","a.field2"]
 pub fn get_unnested_columns(
     col_name: &String,
-    data_type: &DataType,
-) -> Result<Vec<(Column, Arc<Field>)>> {
+    data_type: &LogicalType,
+) -> Result<Vec<(Column, Arc<LogicalField>)>> {
     let mut qualified_columns = Vec::with_capacity(1);
 
     match data_type {
-        DataType::List(field)
-        | DataType::FixedSizeList(field, _)
-        | DataType::LargeList(field) => {
-            let new_field = Arc::new(Field::new(
+        LogicalType::List(field)
+        | LogicalType::FixedSizeList(field, _)
+        | LogicalType::LargeList(field) => {
+            let new_field = Arc::new(LogicalField::new(
                 col_name.clone(),
                 field.data_type().clone(),
                 // Unnesting may produce NULLs even if the list is not null.
@@ -1621,7 +1623,7 @@ pub fn get_unnested_columns(
             // let column = Column::from((None, &new_field));
             qualified_columns.push((column, new_field));
         }
-        DataType::Struct(fields) => {
+        LogicalType::Struct(fields) => {
             qualified_columns.extend(fields.iter().map(|f| {
                 let new_name = format!("{}.{}", col_name, f.name());
                 let column = Column::from_name(&new_name);
@@ -1670,10 +1672,10 @@ pub fn unnest_with_options(
                         original_field.data_type(),
                     )?;
                     match original_field.data_type() {
-                        DataType::List(_)
-                        | DataType::FixedSizeList(_, _)
-                        | DataType::LargeList(_) => list_columns.push(index),
-                        DataType::Struct(_) => struct_columns.push(index),
+                        LogicalType::List(_)
+                        | LogicalType::FixedSizeList(_, _)
+                        | LogicalType::LargeList(_) => list_columns.push(index),
+                        LogicalType::Struct(_) => struct_columns.push(index),
                         _ => {
                             panic!(
                                 "not reachable, should be caught by get_unnested_columns"
@@ -1685,7 +1687,7 @@ pub fn unnest_with_options(
                         .extend(std::iter::repeat(index).take(flatten_columns.len()));
                     Ok(flatten_columns
                         .iter()
-                        .map(|col: &(Column, Arc<Field>)| {
+                        .map(|col: &(Column, Arc<LogicalField>)| {
                             (col.0.relation.to_owned(), col.1.to_owned())
                         })
                         .collect())
@@ -1720,6 +1722,7 @@ pub fn unnest_with_options(
 
 #[cfg(test)]
 mod tests {
+    use arrow::datatypes::{DataType, Field, Fields};
     use super::*;
     use crate::logical_plan::StringifiedPlan;
     use crate::{col, expr, expr_fn::exists, in_subquery, lit, scalar_subquery};
@@ -1752,7 +1755,7 @@ mod tests {
                 .unwrap();
         let expected = DFSchema::try_from_qualified_schema(
             TableReference::bare("employee_csv"),
-            &schema,
+            &schema.clone().into(),
         )
         .unwrap();
         assert_eq!(&expected, plan.schema().as_ref());
@@ -2109,7 +2112,7 @@ mod tests {
 
         // Check unnested field is a scalar
         let field = plan.schema().field_with_name(None, "strings").unwrap();
-        assert_eq!(&DataType::Utf8, field.data_type());
+        assert_eq!(&LogicalType::Utf8, field.data_type());
 
         // Unnesting the singular struct column result into 2 new columns for each subfield
         let plan = nested_table_scan("test_table")?
@@ -2127,7 +2130,7 @@ mod tests {
                 .schema()
                 .field_with_name(None, &format!("struct_singular.{}", field_name))
                 .unwrap();
-            assert_eq!(&DataType::UInt32, field.data_type());
+            assert_eq!(&LogicalType::UInt32, field.data_type());
         }
 
         // Unnesting multiple fields in separate plans
@@ -2146,7 +2149,7 @@ mod tests {
 
         // Check unnested struct list field should be a struct.
         let field = plan.schema().field_with_name(None, "structs").unwrap();
-        assert!(matches!(field.data_type(), DataType::Struct(_)));
+        assert!(matches!(field.data_type(), LogicalType::Struct(_)));
 
         // Unnesting multiple fields at the same time
         let cols = vec!["strings", "structs", "struct_singular"]
@@ -2220,23 +2223,23 @@ mod tests {
 
     #[test]
     fn test_change_redundant_column() -> Result<()> {
-        let t1_field_1 = Field::new("a", DataType::Int32, false);
-        let t2_field_1 = Field::new("a", DataType::Int32, false);
-        let t2_field_3 = Field::new("a", DataType::Int32, false);
-        let t1_field_2 = Field::new("b", DataType::Int32, false);
-        let t2_field_2 = Field::new("b", DataType::Int32, false);
+        let t1_field_1 = LogicalField::new("a", LogicalType::Int32, false);
+        let t2_field_1 = LogicalField::new("a", LogicalType::Int32, false);
+        let t2_field_3 = LogicalField::new("a", LogicalType::Int32, false);
+        let t1_field_2 = LogicalField::new("b", LogicalType::Int32, false);
+        let t2_field_2 = LogicalField::new("b", LogicalType::Int32, false);
 
         let field_vec = vec![t1_field_1, t2_field_1, t1_field_2, t2_field_2, t2_field_3];
-        let remove_redundant = change_redundant_column(&Fields::from(field_vec));
+        let remove_redundant = change_redundant_column(&LogicalFields::from(field_vec));
 
         assert_eq!(
             remove_redundant,
             vec![
-                Field::new("a", DataType::Int32, false),
-                Field::new("a:1", DataType::Int32, false),
-                Field::new("b", DataType::Int32, false),
-                Field::new("b:1", DataType::Int32, false),
-                Field::new("a:2", DataType::Int32, false),
+                LogicalField::new("a", LogicalType::Int32, false),
+                LogicalField::new("a:1", LogicalType::Int32, false),
+                LogicalField::new("b", LogicalType::Int32, false),
+                LogicalField::new("b:1", LogicalType::Int32, false),
+                LogicalField::new("a:2", LogicalType::Int32, false),
             ]
         );
         Ok(())
diff --git a/datafusion/expr/src/logical_plan/ddl.rs b/datafusion/expr/src/logical_plan/ddl.rs
index 45ddbafecfd7..8b938a808b96 100644
--- a/datafusion/expr/src/logical_plan/ddl.rs
+++ b/datafusion/expr/src/logical_plan/ddl.rs
@@ -24,9 +24,9 @@ use std::{
 
 use crate::{Expr, LogicalPlan, Volatility};
 
-use arrow::datatypes::DataType;
 use datafusion_common::{Constraints, DFSchemaRef, SchemaReference, TableReference};
 use sqlparser::ast::Ident;
+use datafusion_common::logical_type::LogicalType;
 
 /// Various types of DDL  (CREATE / DROP) catalog manipulation
 #[derive(Clone, PartialEq, Eq, Hash)]
@@ -322,7 +322,7 @@ pub struct CreateFunction {
     pub temporary: bool,
     pub name: String,
     pub args: Option<Vec<OperateFunctionArg>>,
-    pub return_type: Option<DataType>,
+    pub return_type: Option<LogicalType>,
     pub params: CreateFunctionBody,
     /// Dummy schema
     pub schema: DFSchemaRef,
@@ -332,7 +332,7 @@ pub struct OperateFunctionArg {
     // TODO: figure out how to support mode
     // pub mode: Option<ArgMode>,
     pub name: Option<Ident>,
-    pub data_type: DataType,
+    pub data_type: LogicalType,
     pub default_expr: Option<Expr>,
 }
 #[derive(Clone, PartialEq, Eq, Hash, Debug)]
diff --git a/datafusion/expr/src/logical_plan/dml.rs b/datafusion/expr/src/logical_plan/dml.rs
index c9eef9bd34cc..04124984af3f 100644
--- a/datafusion/expr/src/logical_plan/dml.rs
+++ b/datafusion/expr/src/logical_plan/dml.rs
@@ -20,10 +20,11 @@ use std::fmt::{self, Display};
 use std::hash::{Hash, Hasher};
 use std::sync::Arc;
 
-use arrow::datatypes::{DataType, Field, Schema};
 use datafusion_common::file_options::file_type::FileType;
 use datafusion_common::{DFSchemaRef, TableReference};
-
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 use crate::LogicalPlan;
 
 /// Operator that copies the contents of a database to file(s)
@@ -130,8 +131,6 @@ impl Display for WriteOp {
 
 fn make_count_schema() -> DFSchemaRef {
     Arc::new(
-        Schema::new(vec![Field::new("count", DataType::UInt64, false)])
-            .try_into()
-            .unwrap(),
+        LogicalSchema::new(vec![LogicalField::new("count", LogicalType::UInt64, false)]).try_into().unwrap()
     )
 }
diff --git a/datafusion/expr/src/logical_plan/extension.rs b/datafusion/expr/src/logical_plan/extension.rs
index 2f581c1928f4..182018cbaf65 100644
--- a/datafusion/expr/src/logical_plan/extension.rs
+++ b/datafusion/expr/src/logical_plan/extension.rs
@@ -349,5 +349,5 @@ impl<T: UserDefinedLogicalNodeCore> UserDefinedLogicalNode for T {
 }
 
 fn get_all_columns_from_schema(schema: &DFSchema) -> HashSet<String> {
-    schema.fields().iter().map(|f| f.name().clone()).collect()
+    schema.fields().iter().map(|f| f.name().to_string()).collect()
 }
diff --git a/datafusion/expr/src/logical_plan/plan.rs b/datafusion/expr/src/logical_plan/plan.rs
index 31f830a6a13d..3285f8809d6d 100644
--- a/datafusion/expr/src/logical_plan/plan.rs
+++ b/datafusion/expr/src/logical_plan/plan.rs
@@ -40,7 +40,7 @@ use crate::{
     TableProviderFilterPushDown, TableSource, WindowFunctionDefinition,
 };
 
-use arrow::datatypes::{DataType, Field, Schema, SchemaRef};
+use arrow::datatypes::{DataType, Field, Schema};
 use datafusion_common::tree_node::{
     Transformed, TransformedResult, TreeNode, TreeNodeRecursion,
 };
@@ -55,6 +55,9 @@ use crate::display::PgJsonVisitor;
 use crate::logical_plan::tree_node::unwrap_arc;
 pub use datafusion_common::display::{PlanType, StringifiedPlan, ToStringifiedPlan};
 pub use datafusion_common::{JoinConstraint, JoinType};
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::{LogicalSchema, LogicalSchemaRef};
 
 /// A `LogicalPlan` is a node in a tree of relational operators (such as
 /// Projection or Filter).
@@ -351,20 +354,20 @@ impl LogicalPlan {
     }
 
     /// Returns the (fixed) output schema for explain plans
-    pub fn explain_schema() -> SchemaRef {
-        SchemaRef::new(Schema::new(vec![
+    pub fn explain_schema() -> LogicalSchemaRef {
+        LogicalSchemaRef::new(Schema::new(vec![
             Field::new("plan_type", DataType::Utf8, false),
             Field::new("plan", DataType::Utf8, false),
-        ]))
+        ]).into())
     }
 
     /// Returns the (fixed) output schema for `DESCRIBE` plans
-    pub fn describe_schema() -> Schema {
+    pub fn describe_schema() -> LogicalSchema {
         Schema::new(vec![
             Field::new("column_name", DataType::Utf8, false),
             Field::new("data_type", DataType::Utf8, false),
             Field::new("is_nullable", DataType::Utf8, false),
-        ])
+        ]).into()
     }
 
     /// Returns all expressions (non-recursively) evaluated by the current
@@ -1388,8 +1391,8 @@ impl LogicalPlan {
     /// Walk the logical plan, find any `Placeholder` tokens, and return a map of their IDs and DataTypes
     pub fn get_parameter_types(
         &self,
-    ) -> Result<HashMap<String, Option<DataType>>, DataFusionError> {
-        let mut param_types: HashMap<String, Option<DataType>> = HashMap::new();
+    ) -> Result<HashMap<String, Option<LogicalType>>, DataFusionError> {
+        let mut param_types: HashMap<String, Option<LogicalType>> = HashMap::new();
 
         self.apply_with_subqueries(|plan| {
             plan.apply_expressions(|expr| {
@@ -2085,7 +2088,7 @@ impl SubqueryAlias {
         // functional dependencies:
         let func_dependencies = plan.schema().functional_dependencies().clone();
         let schema = DFSchemaRef::new(
-            DFSchema::try_from_qualified_schema(alias.clone(), &schema)?
+            DFSchema::try_from_qualified_schema(alias.clone(), &schema.into())?
                 .with_functional_dependencies(func_dependencies)?,
         );
         Ok(SubqueryAlias {
@@ -2124,7 +2127,7 @@ impl Filter {
         // construction (such as with correlated subqueries) so we make a best effort here and
         // ignore errors resolving the expression against the schema.
         if let Ok(predicate_type) = predicate.get_type(input.schema()) {
-            if predicate_type != DataType::Boolean {
+            if predicate_type != LogicalType::Boolean {
                 return plan_err!(
                     "Cannot create filter with non-boolean predicate '{predicate}' returning {predicate_type}"
                 );
@@ -2257,7 +2260,7 @@ pub struct Window {
 impl Window {
     /// Create a new window operator.
     pub fn try_new(window_expr: Vec<Expr>, input: Arc<LogicalPlan>) -> Result<Self> {
-        let fields: Vec<(Option<TableReference>, Arc<Field>)> = input
+        let fields: Vec<(Option<TableReference>, Arc<LogicalField>)> = input
             .schema()
             .iter()
             .map(|(q, f)| (q.cloned(), f.clone()))
@@ -2398,7 +2401,7 @@ impl TableScan {
         if table_name.table().is_empty() {
             return plan_err!("table_name cannot be empty");
         }
-        let schema = table_source.schema();
+        let schema: LogicalSchema = table_source.schema().as_ref().clone().into();
         let func_dependencies = FunctionalDependencies::new_from_constraints(
             table_source.constraints(),
             schema.fields.len(),
@@ -2412,7 +2415,7 @@ impl TableScan {
                 let df_schema = DFSchema::new_with_metadata(
                     p.iter()
                         .map(|i| {
-                            (Some(table_name.clone()), Arc::new(schema.field(*i).clone()))
+                            (Some(table_name.clone()), schema.field(*i).clone())
                         })
                         .collect(),
                     schema.metadata.clone(),
@@ -2473,7 +2476,7 @@ pub struct Prepare {
     /// The name of the statement
     pub name: String,
     /// Data types of the parameters ([`Expr::Placeholder`])
-    pub data_types: Vec<DataType>,
+    pub data_types: Vec<LogicalType>,
     /// The logical plan of the statements
     pub input: Arc<LogicalPlan>,
 }
@@ -3494,7 +3497,7 @@ digraph {
         let schema = Arc::new(
             DFSchema::try_from_qualified_schema(
                 TableReference::bare("tab"),
-                &source.schema(),
+                &source.schema().as_ref().clone().into(),
             )
             .unwrap(),
         );
diff --git a/datafusion/expr/src/simplify.rs b/datafusion/expr/src/simplify.rs
index ccf45ff0d048..8c647f16bd75 100644
--- a/datafusion/expr/src/simplify.rs
+++ b/datafusion/expr/src/simplify.rs
@@ -17,9 +17,8 @@
 
 //! Structs and traits to provide the information needed for expression simplification.
 
-use arrow::datatypes::DataType;
 use datafusion_common::{DFSchemaRef, DataFusionError, Result};
-
+use datafusion_common::logical_type::LogicalType;
 use crate::{execution_props::ExecutionProps, Expr, ExprSchemable};
 
 /// Provides the information necessary to apply algebraic simplification to an
@@ -39,7 +38,7 @@ pub trait SimplifyInfo {
     fn execution_props(&self) -> &ExecutionProps;
 
     /// Returns data type of this expr needed for determining optimized int type of a value
-    fn get_data_type(&self, expr: &Expr) -> Result<DataType>;
+    fn get_data_type(&self, expr: &Expr) -> Result<LogicalType>;
 }
 
 /// Provides simplification information based on DFSchema and
@@ -75,7 +74,7 @@ impl<'a> SimplifyInfo for SimplifyContext<'a> {
     /// returns true if this Expr has boolean type
     fn is_boolean_type(&self, expr: &Expr) -> Result<bool> {
         for schema in &self.schema {
-            if let Ok(DataType::Boolean) = expr.get_type(schema) {
+            if let Ok(LogicalType::Boolean) = expr.get_type(schema) {
                 return Ok(true);
             }
         }
@@ -94,7 +93,7 @@ impl<'a> SimplifyInfo for SimplifyContext<'a> {
     }
 
     /// Returns data type of this expr needed for determining optimized int type of a value
-    fn get_data_type(&self, expr: &Expr) -> Result<DataType> {
+    fn get_data_type(&self, expr: &Expr) -> Result<LogicalType> {
         let schema = self.schema.as_ref().ok_or_else(|| {
             DataFusionError::Internal(
                 "attempt to get data type without schema".to_string(),
diff --git a/datafusion/expr/src/type_coercion/binary.rs b/datafusion/expr/src/type_coercion/binary.rs
index 5645a2a4dede..0f144c6ca89b 100644
--- a/datafusion/expr/src/type_coercion/binary.rs
+++ b/datafusion/expr/src/type_coercion/binary.rs
@@ -15,6 +15,8 @@
 // specific language governing permissions and limitations
 // under the License.
 
+// TODO(@notfilippo): make most of these accept LogicalType
+
 //! Coercion rules for matching argument types for binary operators
 
 use std::collections::HashSet;
diff --git a/datafusion/expr/src/type_coercion/functions.rs b/datafusion/expr/src/type_coercion/functions.rs
index 5f060a4a4f16..e6f89efb9dfa 100644
--- a/datafusion/expr/src/type_coercion/functions.rs
+++ b/datafusion/expr/src/type_coercion/functions.rs
@@ -585,7 +585,7 @@ fn coerced_from<'a>(
         // List or LargeList with different dimensions should be handled in TypeSignature or other places before this
         (List(_) | LargeList(_), _)
             if datafusion_common::utils::base_type(type_from).eq(&Null)
-                || list_ndims(type_from) == list_ndims(type_into) =>
+                || list_ndims(&type_from) == list_ndims(&type_into) =>
         {
             Some(type_into.clone())
         }
diff --git a/datafusion/expr/src/type_coercion/mod.rs b/datafusion/expr/src/type_coercion/mod.rs
index 86005da3dafa..275700adc9a1 100644
--- a/datafusion/expr/src/type_coercion/mod.rs
+++ b/datafusion/expr/src/type_coercion/mod.rs
@@ -36,52 +36,53 @@ pub mod binary;
 pub mod functions;
 pub mod other;
 
-use arrow::datatypes::DataType;
+use datafusion_common::logical_type::LogicalType;
+
 /// Determine whether the given data type `dt` represents signed numeric values.
-pub fn is_signed_numeric(dt: &DataType) -> bool {
+pub fn is_signed_numeric(dt: &LogicalType) -> bool {
     matches!(
         dt,
-        DataType::Int8
-            | DataType::Int16
-            | DataType::Int32
-            | DataType::Int64
-            | DataType::Float16
-            | DataType::Float32
-            | DataType::Float64
-            | DataType::Decimal128(_, _)
-            | DataType::Decimal256(_, _),
+        LogicalType::Int8
+            | LogicalType::Int16
+            | LogicalType::Int32
+            | LogicalType::Int64
+            | LogicalType::Float16
+            | LogicalType::Float32
+            | LogicalType::Float64
+            | LogicalType::Decimal128(_, _)
+            | LogicalType::Decimal256(_, _),
     )
 }
 
 /// Determine whether the given data type `dt` is `Null`.
-pub fn is_null(dt: &DataType) -> bool {
-    *dt == DataType::Null
+pub fn is_null(dt: &LogicalType) -> bool {
+    *dt == LogicalType::Null
 }
 
 /// Determine whether the given data type `dt` is a `Timestamp`.
-pub fn is_timestamp(dt: &DataType) -> bool {
-    matches!(dt, DataType::Timestamp(_, _))
+pub fn is_timestamp(dt: &LogicalType) -> bool {
+    matches!(dt, LogicalType::Timestamp(_, _))
 }
 
 /// Determine whether the given data type 'dt' is a `Interval`.
-pub fn is_interval(dt: &DataType) -> bool {
-    matches!(dt, DataType::Interval(_))
+pub fn is_interval(dt: &LogicalType) -> bool {
+    matches!(dt, LogicalType::Interval(_))
 }
 
 /// Determine whether the given data type `dt` is a `Date` or `Timestamp`.
-pub fn is_datetime(dt: &DataType) -> bool {
+pub fn is_datetime(dt: &LogicalType) -> bool {
     matches!(
         dt,
-        DataType::Date32 | DataType::Date64 | DataType::Timestamp(_, _)
+        LogicalType::Date32 | LogicalType::Date64 | LogicalType::Timestamp(_, _)
     )
 }
 
 /// Determine whether the given data type `dt` is a `Utf8` or `LargeUtf8`.
-pub fn is_utf8_or_large_utf8(dt: &DataType) -> bool {
-    matches!(dt, DataType::Utf8 | DataType::LargeUtf8)
+pub fn is_utf8_or_large_utf8(dt: &LogicalType) -> bool {
+    matches!(dt, LogicalType::Utf8 | LogicalType::LargeUtf8)
 }
 
 /// Determine whether the given data type `dt` is a `Decimal`.
-pub fn is_decimal(dt: &DataType) -> bool {
-    matches!(dt, DataType::Decimal128(_, _) | DataType::Decimal256(_, _))
+pub fn is_decimal(dt: &LogicalType) -> bool {
+    matches!(dt, LogicalType::Decimal128(_, _) | LogicalType::Decimal256(_, _))
 }
diff --git a/datafusion/expr/src/utils.rs b/datafusion/expr/src/utils.rs
index 286f05309ea7..3a55297d39ba 100644
--- a/datafusion/expr/src/utils.rs
+++ b/datafusion/expr/src/utils.rs
@@ -28,7 +28,7 @@ use crate::{
     and, BinaryExpr, Expr, ExprSchemable, Filter, GroupingSet, LogicalPlan, Operator,
 };
 
-use arrow::datatypes::{DataType, Field, Schema, TimeUnit};
+use arrow::datatypes::{DataType, TimeUnit};
 use datafusion_common::tree_node::{
     Transformed, TransformedResult, TreeNode, TreeNodeRecursion,
 };
@@ -39,6 +39,9 @@ use datafusion_common::{
 };
 
 use sqlparser::ast::{ExceptSelectItem, ExcludeSelectItem, WildcardAdditionalOptions};
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 ///  The value to which `COUNT(*)` is expanded to in
 ///  `COUNT(<constant>)` expressions
@@ -429,7 +432,7 @@ pub fn expand_qualified_wildcard(
         return plan_err!("Invalid qualifier {qualifier}");
     }
 
-    let qualified_schema = Arc::new(Schema::new(fields_with_qualified));
+    let qualified_schema = Arc::new(LogicalSchema::new(fields_with_qualified));
     let qualified_dfschema =
         DFSchema::try_from_qualified_schema(qualifier.clone(), &qualified_schema)?
             .with_functional_dependencies(projected_func_dependencies)?;
@@ -727,7 +730,7 @@ pub fn from_plan(
 pub fn exprlist_to_fields<'a>(
     exprs: impl IntoIterator<Item = &'a Expr>,
     plan: &LogicalPlan,
-) -> Result<Vec<(Option<TableReference>, Arc<Field>)>> {
+) -> Result<Vec<(Option<TableReference>, Arc<LogicalField>)>> {
     // look for exact match in plan's output schema
     let input_schema = &plan.schema();
     exprs
@@ -830,40 +833,35 @@ pub(crate) fn find_column_indexes_referenced_by_expr(
 /// can this data type be used in hash join equal conditions??
 /// data types here come from function 'equal_rows', if more data types are supported
 /// in equal_rows(hash join), add those data types here to generate join logical plan.
-pub fn can_hash(data_type: &DataType) -> bool {
+pub fn can_hash(data_type: &LogicalType) -> bool {
     match data_type {
-        DataType::Null => true,
-        DataType::Boolean => true,
-        DataType::Int8 => true,
-        DataType::Int16 => true,
-        DataType::Int32 => true,
-        DataType::Int64 => true,
-        DataType::UInt8 => true,
-        DataType::UInt16 => true,
-        DataType::UInt32 => true,
-        DataType::UInt64 => true,
-        DataType::Float32 => true,
-        DataType::Float64 => true,
-        DataType::Timestamp(time_unit, _) => match time_unit {
+        LogicalType::Null => true,
+        LogicalType::Boolean => true,
+        LogicalType::Int8 => true,
+        LogicalType::Int16 => true,
+        LogicalType::Int32 => true,
+        LogicalType::Int64 => true,
+        LogicalType::UInt8 => true,
+        LogicalType::UInt16 => true,
+        LogicalType::UInt32 => true,
+        LogicalType::UInt64 => true,
+        LogicalType::Float32 => true,
+        LogicalType::Float64 => true,
+        LogicalType::Timestamp(time_unit, _) => match time_unit {
             TimeUnit::Second => true,
             TimeUnit::Millisecond => true,
             TimeUnit::Microsecond => true,
             TimeUnit::Nanosecond => true,
         },
-        DataType::Utf8 => true,
-        DataType::LargeUtf8 => true,
-        DataType::Decimal128(_, _) => true,
-        DataType::Date32 => true,
-        DataType::Date64 => true,
-        DataType::FixedSizeBinary(_) => true,
-        DataType::Dictionary(key_type, value_type)
-            if *value_type.as_ref() == DataType::Utf8 =>
-        {
-            DataType::is_dictionary_key_type(key_type)
-        }
-        DataType::List(_) => true,
-        DataType::LargeList(_) => true,
-        DataType::FixedSizeList(_, _) => true,
+        LogicalType::Utf8 => true,
+        LogicalType::LargeUtf8 => true,
+        LogicalType::Decimal128(_, _) => true,
+        LogicalType::Date32 => true,
+        LogicalType::Date64 => true,
+        LogicalType::FixedSizeBinary(_) => true,
+        LogicalType::List(_) => true,
+        LogicalType::LargeList(_) => true,
+        LogicalType::FixedSizeList(_, _) => true,
         _ => false,
     }
 }
@@ -1249,6 +1247,7 @@ impl AggregateOrderSensitivity {
 
 #[cfg(test)]
 mod tests {
+    use datafusion_common::logical_type::LogicalType;
     use super::*;
     use crate::{
         col, cube, expr, expr_vec_fmt, grouping_set, lit, rollup,
@@ -1703,11 +1702,11 @@ mod tests {
     fn test_collect_expr() -> Result<()> {
         let mut accum: HashSet<Column> = HashSet::new();
         expr_to_columns(
-            &Expr::Cast(Cast::new(Box::new(col("a")), DataType::Float64)),
+            &Expr::Cast(Cast::new(Box::new(col("a")), LogicalType::Float64)),
             &mut accum,
         )?;
         expr_to_columns(
-            &Expr::Cast(Cast::new(Box::new(col("a")), DataType::Float64)),
+            &Expr::Cast(Cast::new(Box::new(col("a")), LogicalType::Float64)),
             &mut accum,
         )?;
         assert_eq!(1, accum.len());
diff --git a/datafusion/expr/src/var_provider.rs b/datafusion/expr/src/var_provider.rs
index e00cf7407237..b746955630b3 100644
--- a/datafusion/expr/src/var_provider.rs
+++ b/datafusion/expr/src/var_provider.rs
@@ -17,8 +17,8 @@
 
 //! Variable provider
 
-use arrow::datatypes::DataType;
 use datafusion_common::{Result, ScalarValue};
+use datafusion_common::logical_type::LogicalType;
 
 /// Variable type, system/user defined
 #[derive(Debug, Clone, PartialEq, Eq, Hash)]
@@ -35,7 +35,7 @@ pub trait VarProvider: std::fmt::Debug {
     fn get_value(&self, var_names: Vec<String>) -> Result<ScalarValue>;
 
     /// Return the type of the given variable
-    fn get_type(&self, var_names: &[String]) -> Option<DataType>;
+    fn get_type(&self, var_names: &[String]) -> Option<LogicalType>;
 }
 
 pub fn is_system_variables(variable_names: &[String]) -> bool {
diff --git a/datafusion/functions/src/core/arrow_cast.rs b/datafusion/functions/src/core/arrow_cast.rs
index 9c410d4e18e8..d3200a0a10d0 100644
--- a/datafusion/functions/src/core/arrow_cast.rs
+++ b/datafusion/functions/src/core/arrow_cast.rs
@@ -107,7 +107,7 @@ impl ScalarUDFImpl for ArrowCastFunc {
         info: &dyn SimplifyInfo,
     ) -> Result<ExprSimplifyResult> {
         // convert this into a real cast
-        let target_type = data_type_from_args(&args)?;
+        let target_type = data_type_from_args(&args)?.into();
         // remove second (type) argument
         args.pop().unwrap();
         let arg = args.pop().unwrap();
@@ -130,6 +130,8 @@ impl ScalarUDFImpl for ArrowCastFunc {
 
 /// Returns the requested type from the arguments
 fn data_type_from_args(args: &[Expr]) -> Result<DataType> {
+    // TODO(@notfilippo): maybe parse LogicalType?
+
     if args.len() != 2 {
         return plan_err!("arrow_cast needs 2 arguments, {} provided", args.len());
     }
diff --git a/datafusion/functions/src/core/getfield.rs b/datafusion/functions/src/core/getfield.rs
index b76da15c52ca..8aaae7b740d2 100644
--- a/datafusion/functions/src/core/getfield.rs
+++ b/datafusion/functions/src/core/getfield.rs
@@ -26,6 +26,8 @@ use datafusion_common::{
 use datafusion_expr::{ColumnarValue, Expr, ExprSchemable};
 use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
 use std::any::Any;
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 
 #[derive(Debug)]
 pub struct GetFieldFunc {
@@ -105,35 +107,36 @@ impl ScalarUDFImpl for GetFieldFunc {
                 );
             }
         };
+        // TODO(@notfilippo): avoid converting to physical type
         let data_type = args[0].get_type(schema)?;
         match (data_type, name) {
-            (DataType::Map(fields, _), _) => {
+            (LogicalType::Map(fields, _), _) => {
                 match fields.data_type() {
-                    DataType::Struct(fields) if fields.len() == 2 => {
+                    LogicalType::Struct(fields) if fields.len() == 2 => {
                         // Arrow's MapArray is essentially a ListArray of structs with two columns. They are
                         // often named "key", and "value", but we don't require any specific naming here;
                         // instead, we assume that the second columnis the "value" column both here and in
                         // execution.
                         let value_field = fields.get(1).expect("fields should have exactly two members");
-                        Ok(value_field.data_type().clone())
+                        Ok(value_field.data_type().physical_type())
                     },
                     _ => plan_err!("Map fields must contain a Struct with exactly 2 fields"),
                 }
             }
-            (DataType::Struct(fields), ScalarValue::Utf8(Some(s))) => {
+            (LogicalType::Struct(fields), ScalarValue::Utf8(Some(s))) => {
                 if s.is_empty() {
                     plan_err!(
                         "Struct based indexed access requires a non empty string"
                     )
                 } else {
                     let field = fields.iter().find(|f| f.name() == s);
-                    field.ok_or(plan_datafusion_err!("Field {s} not found in struct")).map(|f| f.data_type().clone())
+                    field.ok_or(plan_datafusion_err!("Field {s} not found in struct")).map(|f| f.data_type().clone().physical_type())
                 }
             }
-            (DataType::Struct(_), _) => plan_err!(
+            (LogicalType::Struct(_), _) => plan_err!(
                 "Only UTF8 strings are valid as an indexed field in a struct"
             ),
-            (DataType::Null, _) => Ok(DataType::Null),
+            (LogicalType::Null, _) => Ok(DataType::Null),
             (other, _) => plan_err!("The expression to get an indexed field is only valid for `List`, `Struct`, `Map` or `Null` types, got {other}"),
         }
     }
diff --git a/datafusion/functions/src/core/named_struct.rs b/datafusion/functions/src/core/named_struct.rs
index 8ccda977f3a4..eeadd18c6215 100644
--- a/datafusion/functions/src/core/named_struct.rs
+++ b/datafusion/functions/src/core/named_struct.rs
@@ -22,6 +22,7 @@ use datafusion_expr::{ColumnarValue, Expr, ExprSchemable};
 use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
 use std::any::Any;
 use std::sync::Arc;
+use datafusion_common::logical_type::extension::ExtensionType;
 
 /// put values in a struct array.
 fn named_struct_expr(args: &[ColumnarValue]) -> Result<ColumnarValue> {
@@ -139,7 +140,7 @@ impl ScalarUDFImpl for NamedStructFunc {
                 let value = &chunk[1];
 
                 if let Expr::Literal(ScalarValue::Utf8(Some(name))) = name {
-                    Ok(Field::new(name, value.get_type(schema)?, true))
+                    Ok(Field::new(name, value.get_type(schema)?.physical_type(), true))
                 } else {
                     exec_err!("named_struct even arguments must be string literals, got {name} instead at position {}", i * 2)
                 }
diff --git a/datafusion/functions/src/math/log.rs b/datafusion/functions/src/math/log.rs
index 0791561539e1..0d4d66eb5e42 100644
--- a/datafusion/functions/src/math/log.rs
+++ b/datafusion/functions/src/math/log.rs
@@ -28,6 +28,7 @@ use datafusion_common::{
     exec_err, internal_err, plan_datafusion_err, plan_err, DataFusionError, Result,
     ScalarValue,
 };
+use datafusion_common::logical_type::extension::ExtensionType;
 use datafusion_expr::expr::ScalarFunction;
 use datafusion_expr::simplify::{ExprSimplifyResult, SimplifyInfo};
 use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
@@ -158,6 +159,7 @@ impl ScalarUDFImpl for LogFunc {
         Ok(ColumnarValue::Array(arr))
     }
 
+    // TODO(@notfilippo): avoid converting to physical type
     /// Simplify the `log` function by the relevant rules:
     /// 1. Log(a, 1) ===> 0
     /// 2. Log(a, Power(a, b)) ===> b
@@ -182,13 +184,13 @@ impl ScalarUDFImpl for LogFunc {
         let base = if let Some(base) = args.pop() {
             base
         } else {
-            lit(ScalarValue::new_ten(&number_datatype)?)
+            lit(ScalarValue::new_ten(&number_datatype.physical_type())?)
         };
 
         match number {
-            Expr::Literal(value) if value == ScalarValue::new_one(&number_datatype)? => {
+            Expr::Literal(value) if value == ScalarValue::new_one(&number_datatype.physical_type())? => {
                 Ok(ExprSimplifyResult::Simplified(lit(ScalarValue::new_zero(
-                    &info.get_data_type(&base)?,
+                    &info.get_data_type(&base)?.physical_type(),
                 )?)))
             }
             Expr::ScalarFunction(ScalarFunction { func, mut args })
@@ -200,7 +202,7 @@ impl ScalarUDFImpl for LogFunc {
             number => {
                 if number == base {
                     Ok(ExprSimplifyResult::Simplified(lit(ScalarValue::new_one(
-                        &number_datatype,
+                        &number_datatype.physical_type(),
                     )?)))
                 } else {
                     let args = match num_args {
diff --git a/datafusion/functions/src/math/power.rs b/datafusion/functions/src/math/power.rs
index 5b790fb56ddf..77a131997c41 100644
--- a/datafusion/functions/src/math/power.rs
+++ b/datafusion/functions/src/math/power.rs
@@ -32,7 +32,7 @@ use datafusion_expr::TypeSignature::*;
 use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
 use std::any::Any;
 use std::sync::Arc;
-
+use datafusion_common::logical_type::extension::ExtensionType;
 use super::log::LogFunc;
 
 #[derive(Debug)]
@@ -127,6 +127,7 @@ impl ScalarUDFImpl for PowerFunc {
         Ok(ColumnarValue::Array(arr))
     }
 
+    // TODO(@notfilippo): avoid converting to physical type
     /// Simplify the `power` function by the relevant rules:
     /// 1. Power(a, 0) ===> 0
     /// 2. Power(a, 1) ===> a
@@ -143,11 +144,11 @@ impl ScalarUDFImpl for PowerFunc {
             plan_datafusion_err!("Expected power to have 2 arguments, got 1")
         })?;
 
-        let exponent_type = info.get_data_type(&exponent)?;
+        let exponent_type = info.get_data_type(&exponent)?.physical_type();
         match exponent {
             Expr::Literal(value) if value == ScalarValue::new_zero(&exponent_type)? => {
                 Ok(ExprSimplifyResult::Simplified(Expr::Literal(
-                    ScalarValue::new_one(&info.get_data_type(&base)?)?,
+                    ScalarValue::new_one(&info.get_data_type(&base)?.physical_type())?,
                 )))
             }
             Expr::Literal(value) if value == ScalarValue::new_one(&exponent_type)? => {
diff --git a/datafusion/optimizer/src/analyzer/count_wildcard_rule.rs b/datafusion/optimizer/src/analyzer/count_wildcard_rule.rs
index 34f9802b1fd9..1074c04aa395 100644
--- a/datafusion/optimizer/src/analyzer/count_wildcard_rule.rs
+++ b/datafusion/optimizer/src/analyzer/count_wildcard_rule.rs
@@ -98,7 +98,6 @@ fn analyze_internal(plan: LogicalPlan) -> Result<Transformed<LogicalPlan>> {
 mod tests {
     use super::*;
     use crate::test::*;
-    use arrow::datatypes::DataType;
     use datafusion_common::ScalarValue;
     use datafusion_expr::expr::Sort;
     use datafusion_expr::{
@@ -108,7 +107,7 @@ mod tests {
     };
     use datafusion_functions_aggregate::count::count_udaf;
     use std::sync::Arc;
-
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_functions_aggregate::expr_fn::{count, sum};
 
     fn assert_plan_eq(plan: LogicalPlan, expected: &str) -> Result<()> {
@@ -192,7 +191,7 @@ mod tests {
             .filter(
                 scalar_subquery(Arc::new(
                     LogicalPlanBuilder::from(table_scan_t2)
-                        .filter(out_ref_col(DataType::UInt32, "t1.a").eq(col("t2.a")))?
+                        .filter(out_ref_col(LogicalType::UInt32, "t1.a").eq(col("t2.a")))?
                         .aggregate(
                             Vec::<Expr>::new(),
                             vec![count(lit(COUNT_STAR_EXPANSION))],
diff --git a/datafusion/optimizer/src/analyzer/function_rewrite.rs b/datafusion/optimizer/src/analyzer/function_rewrite.rs
index 098c934bf7e1..86d106bb8975 100644
--- a/datafusion/optimizer/src/analyzer/function_rewrite.rs
+++ b/datafusion/optimizer/src/analyzer/function_rewrite.rs
@@ -53,7 +53,7 @@ impl ApplyFunctionRewrites {
         if let LogicalPlan::TableScan(ts) = &plan {
             let source_schema = DFSchema::try_from_qualified_schema(
                 ts.table_name.clone(),
-                &ts.source.schema(),
+                &ts.source.schema().as_ref().clone().into(),
             )?;
             schema.merge(&source_schema);
         }
diff --git a/datafusion/optimizer/src/analyzer/type_coercion.rs b/datafusion/optimizer/src/analyzer/type_coercion.rs
index 51ec8d8af1d3..9671f849ce2a 100644
--- a/datafusion/optimizer/src/analyzer/type_coercion.rs
+++ b/datafusion/optimizer/src/analyzer/type_coercion.rs
@@ -27,6 +27,8 @@ use datafusion_common::{
     exec_err, internal_err, not_impl_err, plan_datafusion_err, plan_err, DFSchema,
     DataFusionError, Result, ScalarValue,
 };
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::expr::{
     self, AggregateFunctionDefinition, Between, BinaryExpr, Case, Exists, InList,
     InSubquery, Like, ScalarFunction, WindowFunction,
@@ -93,7 +95,7 @@ fn analyze_internal(
     if let LogicalPlan::TableScan(ts) = &plan {
         let source_schema = DFSchema::try_from_qualified_schema(
             ts.table_name.clone(),
-            &ts.source.schema(),
+            &ts.source.schema().as_ref().clone().into(),
         )?;
         schema.merge(&source_schema);
     }
@@ -161,13 +163,13 @@ impl<'a> TypeCoercionRewriter<'a> {
         right: Expr,
     ) -> Result<(Expr, Expr)> {
         let (left_type, right_type) = get_input_types(
-            &left.get_type(self.schema)?,
+            &left.get_type(self.schema)?.physical_type(),
             op,
-            &right.get_type(self.schema)?,
+            &right.get_type(self.schema)?.physical_type(),
         )?;
         Ok((
-            left.cast_to(&left_type, self.schema)?,
-            right.cast_to(&right_type, self.schema)?,
+            left.cast_to(&left_type.into(), self.schema)?,
+            right.cast_to(&right_type.into(), self.schema)?,
         ))
     }
 }
@@ -210,7 +212,7 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                     analyze_internal(self.schema, unwrap_arc(subquery.subquery))?.data;
                 let expr_type = expr.get_type(self.schema)?;
                 let subquery_type = new_plan.schema().field(0).data_type();
-                let common_type = comparison_coercion(&expr_type, subquery_type).ok_or(plan_datafusion_err!(
+                let common_type = comparison_coercion(&expr_type.physical_type(), &subquery_type.physical_type()).ok_or(plan_datafusion_err!(
                         "expr type {expr_type:?} can't cast to {subquery_type:?} in InSubquery"
                     ),
                 )?;
@@ -219,8 +221,8 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                     outer_ref_columns: subquery.outer_ref_columns,
                 };
                 Ok(Transformed::yes(Expr::InSubquery(InSubquery::new(
-                    Box::new(expr.cast_to(&common_type, self.schema)?),
-                    cast_subquery(new_subquery, &common_type)?,
+                    Box::new(expr.cast_to(&common_type.clone().into(), self.schema)?),
+                    cast_subquery(new_subquery, &common_type.into())?,
                     negated,
                 ))))
             }
@@ -255,7 +257,7 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
             }) => {
                 let left_type = expr.get_type(self.schema)?;
                 let right_type = pattern.get_type(self.schema)?;
-                let coerced_type = like_coercion(&left_type,  &right_type).ok_or_else(|| {
+                let coerced_type = like_coercion(&left_type.physical_type(),  &right_type.physical_type()).ok_or_else(|| {
                     let op_name = if case_insensitive {
                         "ILIKE"
                     } else {
@@ -266,10 +268,9 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                     )
                 })?;
                 let expr = match left_type {
-                    DataType::Dictionary(_, inner) if *inner == DataType::Utf8 => expr,
-                    _ => Box::new(expr.cast_to(&coerced_type, self.schema)?),
+                    _ => Box::new(expr.cast_to(&coerced_type.clone().into(), self.schema)?),
                 };
-                let pattern = Box::new(pattern.cast_to(&coerced_type, self.schema)?);
+                let pattern = Box::new(pattern.cast_to(&coerced_type.into(), self.schema)?);
                 Ok(Transformed::yes(Expr::Like(Like::new(
                     negated,
                     expr,
@@ -294,14 +295,14 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
             }) => {
                 let expr_type = expr.get_type(self.schema)?;
                 let low_type = low.get_type(self.schema)?;
-                let low_coerced_type = comparison_coercion(&expr_type, &low_type)
+                let low_coerced_type = comparison_coercion(&expr_type.physical_type(), &low_type.physical_type())
                     .ok_or_else(|| {
                         DataFusionError::Internal(format!(
                             "Failed to coerce types {expr_type} and {low_type} in BETWEEN expression"
                         ))
                     })?;
                 let high_type = high.get_type(self.schema)?;
-                let high_coerced_type = comparison_coercion(&expr_type, &low_type)
+                let high_coerced_type = comparison_coercion(&expr_type.physical_type(), &low_type.physical_type())
                     .ok_or_else(|| {
                         DataFusionError::Internal(format!(
                             "Failed to coerce types {expr_type} and {high_type} in BETWEEN expression"
@@ -313,7 +314,7 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                             DataFusionError::Internal(format!(
                                 "Failed to coerce types {expr_type} and {high_type} in BETWEEN expression"
                             ))
-                        })?;
+                        })?.into();
                 Ok(Transformed::yes(Expr::Between(Between::new(
                     Box::new(expr.cast_to(&coercion_type, self.schema)?),
                     negated,
@@ -326,24 +327,26 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
                 list,
                 negated,
             }) => {
+                println!("{:?}", self.schema);
                 let expr_data_type = expr.get_type(self.schema)?;
                 let list_data_types = list
                     .iter()
-                    .map(|list_expr| list_expr.get_type(self.schema))
+                    .map(|list_expr| list_expr.get_type(self.schema).map(|t| t.physical_type()))
                     .collect::<Result<Vec<_>>>()?;
                 let result_type =
-                    get_coerce_type_for_list(&expr_data_type, &list_data_types);
+                    get_coerce_type_for_list(&expr_data_type.physical_type(), &list_data_types);
                 match result_type {
                     None => plan_err!(
                         "Can not find compatible types to compare {expr_data_type:?} with {list_data_types:?}"
                     ),
                     Some(coerced_type) => {
                         // find the coerced type
-                        let cast_expr = expr.cast_to(&coerced_type, self.schema)?;
+                        let logical_coerced_type = coerced_type.into();
+                        let cast_expr = expr.cast_to(&logical_coerced_type, self.schema)?;
                         let cast_list_expr = list
                             .into_iter()
                             .map(|list_expr| {
-                                list_expr.cast_to(&coerced_type, self.schema)
+                                list_expr.cast_to(&logical_coerced_type, self.schema)
                             })
                             .collect::<Result<Vec<_>>>()?;
                         Ok(Transformed::yes(Expr::InList(InList ::new(
@@ -473,11 +476,11 @@ impl<'a> TreeNodeRewriter for TypeCoercionRewriter<'a> {
 
 /// Casts the given `value` to `target_type`. Note that this function
 /// only considers `Null` or `Utf8` values.
-fn coerce_scalar(target_type: &DataType, value: &ScalarValue) -> Result<ScalarValue> {
+fn coerce_scalar(target_type: &LogicalType, value: &ScalarValue) -> Result<ScalarValue> {
     match value {
         // Coerce Utf8 values:
         ScalarValue::Utf8(Some(val)) => {
-            ScalarValue::try_from_string(val.clone(), target_type)
+            ScalarValue::try_from_string(val.clone(), &target_type.physical_type())
         }
         s => {
             if s.is_null() {
@@ -500,7 +503,7 @@ fn coerce_scalar(target_type: &DataType, value: &ScalarValue) -> Result<ScalarVa
 /// family), we return a `Null` value of this type to signal this situation.
 /// Downstream code uses this signal to treat these values as *unbounded*.
 fn coerce_scalar_range_aware(
-    target_type: &DataType,
+    target_type: &LogicalType,
     value: ScalarValue,
 ) -> Result<ScalarValue> {
     coerce_scalar(target_type, &value).or_else(|err| {
@@ -519,18 +522,18 @@ fn coerce_scalar_range_aware(
 /// This function returns the widest type in the family of `given_type`.
 /// If the given type is already the widest type, it returns `None`.
 /// For example, if `given_type` is `Int8`, it returns `Int64`.
-fn get_widest_type_in_family(given_type: &DataType) -> Option<&DataType> {
+fn get_widest_type_in_family(given_type: &LogicalType) -> Option<&LogicalType> {
     match given_type {
-        DataType::UInt8 | DataType::UInt16 | DataType::UInt32 => Some(&DataType::UInt64),
-        DataType::Int8 | DataType::Int16 | DataType::Int32 => Some(&DataType::Int64),
-        DataType::Float16 | DataType::Float32 => Some(&DataType::Float64),
+        LogicalType::UInt8 | LogicalType::UInt16 | LogicalType::UInt32 => Some(&LogicalType::UInt64),
+        LogicalType::Int8 | LogicalType::Int16 | LogicalType::Int32 => Some(&LogicalType::Int64),
+        LogicalType::Float16 | LogicalType::Float32 => Some(&LogicalType::Float64),
         _ => None,
     }
 }
 
 /// Coerces the given (window frame) `bound` to `target_type`.
 fn coerce_frame_bound(
-    target_type: &DataType,
+    target_type: &LogicalType,
     bound: WindowFrameBound,
 ) -> Result<WindowFrameBound> {
     match bound {
@@ -561,11 +564,11 @@ fn coerce_window_frame(
             if let Some(col_type) = current_types.first() {
                 if col_type.is_numeric()
                     || is_utf8_or_large_utf8(col_type)
-                    || matches!(col_type, DataType::Null)
+                    || matches!(col_type, LogicalType::Null)
                 {
                     col_type
                 } else if is_datetime(col_type) {
-                    &DataType::Interval(IntervalUnit::MonthDayNano)
+                    &LogicalType::Interval(IntervalUnit::MonthDayNano)
                 } else {
                     return internal_err!(
                         "Cannot run range queries on datatype: {col_type:?}"
@@ -575,7 +578,7 @@ fn coerce_window_frame(
                 return internal_err!("ORDER BY column cannot be empty");
             }
         }
-        WindowFrameUnits::Rows | WindowFrameUnits::Groups => &DataType::UInt64,
+        WindowFrameUnits::Rows | WindowFrameUnits::Groups => &LogicalType::UInt64,
     };
     window_frame.start_bound = coerce_frame_bound(target_type, window_frame.start_bound)?;
     window_frame.end_bound = coerce_frame_bound(target_type, window_frame.end_bound)?;
@@ -586,8 +589,8 @@ fn coerce_window_frame(
 // The above op will be rewrite to the binary op when creating the physical op.
 fn get_casted_expr_for_bool_op(expr: Expr, schema: &DFSchema) -> Result<Expr> {
     let left_type = expr.get_type(schema)?;
-    get_input_types(&left_type, &Operator::IsDistinctFrom, &DataType::Boolean)?;
-    expr.cast_to(&DataType::Boolean, schema)
+    get_input_types(&left_type.physical_type(), &Operator::IsDistinctFrom, &DataType::Boolean)?;
+    expr.cast_to(&LogicalType::Boolean, schema)
 }
 
 /// Returns `expressions` coerced to types compatible with
@@ -605,15 +608,15 @@ fn coerce_arguments_for_signature_with_scalar_udf(
 
     let current_types = expressions
         .iter()
-        .map(|e| e.get_type(schema))
+        .map(|e| e.get_type(schema).map(|t| t.physical_type()))
         .collect::<Result<Vec<_>>>()?;
 
     let new_types = data_types_with_scalar_udf(&current_types, func)?;
 
     expressions
         .into_iter()
-        .enumerate()
-        .map(|(i, expr)| expr.cast_to(&new_types[i], schema))
+        .zip(new_types)
+        .map(|(expr, t)| expr.cast_to(&t.into(), schema))
         .collect()
 }
 
@@ -632,15 +635,15 @@ fn coerce_arguments_for_signature_with_aggregate_udf(
 
     let current_types = expressions
         .iter()
-        .map(|e| e.get_type(schema))
+        .map(|e| e.get_type(schema).map(|t| t.physical_type()))
         .collect::<Result<Vec<_>>>()?;
 
     let new_types = data_types_with_aggregate_udf(&current_types, func)?;
 
     expressions
         .into_iter()
-        .enumerate()
-        .map(|(i, expr)| expr.cast_to(&new_types[i], schema))
+        .zip(new_types)
+        .map(|(expr, t)| expr.cast_to(&t.into(), schema))
         .collect()
 }
 
@@ -655,8 +658,8 @@ fn coerce_arguments_for_fun(
             .into_iter()
             .map(|expr| {
                 let data_type = expr.get_type(schema).unwrap();
-                if let DataType::FixedSizeList(field, _) = data_type {
-                    let to_type = DataType::List(field.clone());
+                if let LogicalType::FixedSizeList(field, _) = data_type {
+                    let to_type = LogicalType::List(field.clone());
                     expr.cast_to(&to_type, schema)
                 } else {
                     Ok(expr)
@@ -682,7 +685,7 @@ fn coerce_agg_exprs_for_signature(
     }
     let current_types = input_exprs
         .iter()
-        .map(|e| e.get_type(schema))
+        .map(|e| e.get_type(schema).map(|t| t.physical_type()))
         .collect::<Result<Vec<_>>>()?;
 
     let coerced_types =
@@ -690,8 +693,8 @@ fn coerce_agg_exprs_for_signature(
 
     input_exprs
         .into_iter()
-        .enumerate()
-        .map(|(i, expr)| expr.cast_to(&coerced_types[i], schema))
+        .zip(coerced_types)
+        .map(|(expr, t)| expr.cast_to(&t.into(), schema))
         .collect()
 }
 
@@ -735,12 +738,12 @@ fn coerce_case_expression(case: Case, schema: &DFSchema) -> Result<Case> {
     let then_types = case
         .when_then_expr
         .iter()
-        .map(|(_when, then)| then.get_type(schema))
+        .map(|(_when, then)| then.get_type(schema).map(|t| t.physical_type()))
         .collect::<Result<Vec<_>>>()?;
     let else_type = case
         .else_expr
         .as_ref()
-        .map(|expr| expr.get_type(schema))
+        .map(|expr| expr.get_type(schema).map(|t| t.physical_type()))
         .transpose()?;
 
     // find common coercible types
@@ -750,10 +753,10 @@ fn coerce_case_expression(case: Case, schema: &DFSchema) -> Result<Case> {
             let when_types = case
                 .when_then_expr
                 .iter()
-                .map(|(when, _then)| when.get_type(schema))
+                .map(|(when, _then)| when.get_type(schema).map(|t| t.physical_type()))
                 .collect::<Result<Vec<_>>>()?;
             let coerced_type =
-                get_coerce_type_for_case_expression(&when_types, Some(case_type));
+                get_coerce_type_for_case_expression(&when_types, Some(&case_type.physical_type()));
             coerced_type.ok_or_else(|| {
                 plan_datafusion_err!(
                     "Failed to coerce case ({case_type:?}) and when ({when_types:?}) \
@@ -776,7 +779,7 @@ fn coerce_case_expression(case: Case, schema: &DFSchema) -> Result<Case> {
     let case_expr = case
         .expr
         .zip(case_when_coerce_type.as_ref())
-        .map(|(case_expr, coercible_type)| case_expr.cast_to(coercible_type, schema))
+        .map(|(case_expr, coercible_type)| case_expr.cast_to(&coercible_type.into(), schema))
         .transpose()?
         .map(Box::new);
     let when_then = case
@@ -784,7 +787,7 @@ fn coerce_case_expression(case: Case, schema: &DFSchema) -> Result<Case> {
         .into_iter()
         .map(|(when, then)| {
             let when_type = case_when_coerce_type.as_ref().unwrap_or(&DataType::Boolean);
-            let when = when.cast_to(when_type, schema).map_err(|e| {
+            let when = when.cast_to(&when_type.into(), schema).map_err(|e| {
                 DataFusionError::Context(
                     format!(
                         "WHEN expressions in CASE couldn't be \
@@ -793,13 +796,13 @@ fn coerce_case_expression(case: Case, schema: &DFSchema) -> Result<Case> {
                     Box::new(e),
                 )
             })?;
-            let then = then.cast_to(&then_else_coerce_type, schema)?;
+            let then = then.cast_to(&then_else_coerce_type.clone().into(), schema)?;
             Ok((Box::new(when), Box::new(then)))
         })
         .collect::<Result<Vec<_>>>()?;
     let else_expr = case
         .else_expr
-        .map(|expr| expr.cast_to(&then_else_coerce_type, schema))
+        .map(|expr| expr.cast_to(&then_else_coerce_type.into(), schema))
         .transpose()?
         .map(Box::new);
 
@@ -816,6 +819,8 @@ mod test {
 
     use datafusion_common::tree_node::{TransformedResult, TreeNode};
     use datafusion_common::{DFSchema, DFSchemaRef, Result, ScalarValue};
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::expr::{self, InSubquery, Like, ScalarFunction};
     use datafusion_expr::logical_plan::{EmptyRelation, Projection};
     use datafusion_expr::test::function_stub::avg_udaf;
@@ -839,12 +844,12 @@ mod test {
         }))
     }
 
-    fn empty_with_type(data_type: DataType) -> Arc<LogicalPlan> {
+    fn empty_with_type(data_type: LogicalType) -> Arc<LogicalPlan> {
         Arc::new(LogicalPlan::EmptyRelation(EmptyRelation {
             produce_one_row: false,
             schema: Arc::new(
                 DFSchema::from_unqualifed_fields(
-                    vec![Field::new("a", data_type, true)].into(),
+                    vec![LogicalField::new("a", data_type, true)].into(),
                     std::collections::HashMap::new(),
                 )
                 .unwrap(),
@@ -855,7 +860,7 @@ mod test {
     #[test]
     fn simple_case() -> Result<()> {
         let expr = col("a").lt(lit(2_u32));
-        let empty = empty_with_type(DataType::Float64);
+        let empty = empty_with_type(LogicalType::Float64);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected = "Projection: a < CAST(UInt32(2) AS Float64)\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)
@@ -864,7 +869,7 @@ mod test {
     #[test]
     fn nested_case() -> Result<()> {
         let expr = col("a").lt(lit(2_u32));
-        let empty = empty_with_type(DataType::Float64);
+        let empty = empty_with_type(LogicalType::Float64);
 
         let plan = LogicalPlan::Projection(Projection::try_new(
             vec![expr.clone().or(expr)],
@@ -894,7 +899,7 @@ mod test {
         }
 
         fn return_type(&self, _args: &[DataType]) -> Result<DataType> {
-            Ok(DataType::Utf8)
+            Ok(Utf8)
         }
 
         fn invoke(&self, _args: &[ColumnarValue]) -> Result<ColumnarValue> {
@@ -1019,10 +1024,10 @@ mod test {
         let expected = "Projection: avg(Float64(12))\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
 
-        let empty = empty_with_type(DataType::Int32);
+        let empty = empty_with_type(LogicalType::Int32);
         let agg_expr = Expr::AggregateFunction(expr::AggregateFunction::new_udf(
             avg_udaf(),
-            vec![cast(col("a"), DataType::Float64)],
+            vec![cast(col("a"), LogicalType::Float64)],
             false,
             None,
             None,
@@ -1056,7 +1061,7 @@ mod test {
     #[test]
     fn binary_op_date32_op_interval() -> Result<()> {
         // CAST(Utf8("1998-03-18") AS Date32) + IntervalDayTime("...")
-        let expr = cast(lit("1998-03-18"), DataType::Date32)
+        let expr = cast(lit("1998-03-18"), LogicalType::Date32)
             + lit(ScalarValue::new_interval_dt(123, 456));
         let empty = empty();
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
@@ -1070,7 +1075,7 @@ mod test {
     fn inlist_case() -> Result<()> {
         // a in (1,4,8), a is int64
         let expr = col("a").in_list(vec![lit(1_i32), lit(4_i8), lit(8_i64)], false);
-        let empty = empty_with_type(DataType::Int64);
+        let empty = empty_with_type(LogicalType::Int64);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected =
             "Projection: a IN ([CAST(Int32(1) AS Int64), CAST(Int8(4) AS Int64), Int64(8)]) AS a IN (Map { iter: Iter([Literal(Int32(1)), Literal(Int8(4)), Literal(Int64(8))]) })\
@@ -1082,7 +1087,7 @@ mod test {
         let empty = Arc::new(LogicalPlan::EmptyRelation(EmptyRelation {
             produce_one_row: false,
             schema: Arc::new(DFSchema::from_unqualifed_fields(
-                vec![Field::new("a", DataType::Decimal128(12, 4), true)].into(),
+                vec![LogicalField::new("a", LogicalType::Decimal128(12, 4), true)].into(),
                 std::collections::HashMap::new(),
             )?),
         }));
@@ -1098,10 +1103,10 @@ mod test {
         let expr = col("a").between(
             lit("2002-05-08"),
             // (cast('2002-05-08' as date) + interval '1 months')
-            cast(lit("2002-05-08"), DataType::Date32)
+            cast(lit("2002-05-08"), LogicalType::Date32)
                 + lit(ScalarValue::new_interval_ym(0, 1)),
         );
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Filter(Filter::try_new(expr, empty)?);
         let expected =
             "Filter: a BETWEEN Utf8(\"2002-05-08\") AND CAST(CAST(Utf8(\"2002-05-08\") AS Date32) + IntervalYearMonth(\"1\") AS Utf8)\
@@ -1113,11 +1118,11 @@ mod test {
     fn between_infer_cheap_type() -> Result<()> {
         let expr = col("a").between(
             // (cast('2002-05-08' as date) + interval '1 months')
-            cast(lit("2002-05-08"), DataType::Date32)
+            cast(lit("2002-05-08"), LogicalType::Date32)
                 + lit(ScalarValue::new_interval_ym(0, 1)),
             lit("2002-12-08"),
         );
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Filter(Filter::try_new(expr, empty)?);
         // TODO: we should cast col(a).
         let expected =
@@ -1130,13 +1135,13 @@ mod test {
     fn is_bool_for_type_coercion() -> Result<()> {
         // is true
         let expr = col("a").is_true();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan =
             LogicalPlan::Projection(Projection::try_new(vec![expr.clone()], empty)?);
         let expected = "Projection: a IS TRUE\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
 
-        let empty = empty_with_type(DataType::Int64);
+        let empty = empty_with_type(LogicalType::Int64);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let ret = assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, "");
         let err = ret.unwrap_err().to_string();
@@ -1144,21 +1149,21 @@ mod test {
 
         // is not true
         let expr = col("a").is_not_true();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected = "Projection: a IS NOT TRUE\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
 
         // is false
         let expr = col("a").is_false();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected = "Projection: a IS FALSE\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
 
         // is not false
         let expr = col("a").is_not_false();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected = "Projection: a IS NOT FALSE\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
@@ -1172,7 +1177,7 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::new_utf8("abc")));
         let like_expr = Expr::Like(Like::new(false, expr, pattern, None, false));
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![like_expr], empty)?);
         let expected = "Projection: a LIKE Utf8(\"abc\")\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
@@ -1180,7 +1185,7 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::Null));
         let like_expr = Expr::Like(Like::new(false, expr, pattern, None, false));
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![like_expr], empty)?);
         let expected = "Projection: a LIKE CAST(NULL AS Utf8) AS a LIKE NULL\
              \n  EmptyRelation";
@@ -1189,10 +1194,11 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::new_utf8("abc")));
         let like_expr = Expr::Like(Like::new(false, expr, pattern, None, false));
-        let empty = empty_with_type(DataType::Int64);
+        let empty = empty_with_type(LogicalType::Int64);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![like_expr], empty)?);
         let err = assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected);
         assert!(err.is_err());
+        println!("{:?}", err);
         assert!(err.unwrap_err().to_string().contains(
             "There isn't a common type to coerce Int64 and Utf8 in LIKE expression"
         ));
@@ -1201,7 +1207,7 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::new_utf8("abc")));
         let ilike_expr = Expr::Like(Like::new(false, expr, pattern, None, true));
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![ilike_expr], empty)?);
         let expected = "Projection: a ILIKE Utf8(\"abc\")\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
@@ -1209,7 +1215,7 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::Null));
         let ilike_expr = Expr::Like(Like::new(false, expr, pattern, None, true));
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![ilike_expr], empty)?);
         let expected = "Projection: a ILIKE CAST(NULL AS Utf8) AS a ILIKE NULL\
              \n  EmptyRelation";
@@ -1218,7 +1224,7 @@ mod test {
         let expr = Box::new(col("a"));
         let pattern = Box::new(lit(ScalarValue::new_utf8("abc")));
         let ilike_expr = Expr::Like(Like::new(false, expr, pattern, None, true));
-        let empty = empty_with_type(DataType::Int64);
+        let empty = empty_with_type(LogicalType::Int64);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![ilike_expr], empty)?);
         let err = assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected);
         assert!(err.is_err());
@@ -1232,13 +1238,13 @@ mod test {
     fn unknown_for_type_coercion() -> Result<()> {
         // unknown
         let expr = col("a").is_unknown();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan =
             LogicalPlan::Projection(Projection::try_new(vec![expr.clone()], empty)?);
         let expected = "Projection: a IS UNKNOWN\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
 
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let ret = assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected);
         let err = ret.unwrap_err().to_string();
@@ -1246,7 +1252,7 @@ mod test {
 
         // is not unknown
         let expr = col("a").is_not_unknown();
-        let empty = empty_with_type(DataType::Boolean);
+        let empty = empty_with_type(LogicalType::Boolean);
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         let expected = "Projection: a IS NOT UNKNOWN\n  EmptyRelation";
         assert_analyzed_plan_eq(Arc::new(TypeCoercion::new()), plan, expected)?;
@@ -1256,7 +1262,7 @@ mod test {
 
     #[test]
     fn concat_for_type_coercion() -> Result<()> {
-        let empty = empty_with_type(DataType::Utf8);
+        let empty = empty_with_type(LogicalType::Utf8);
         let args = [col("a"), lit("b"), lit(true), lit(false), lit(13)];
 
         // concat-type signature
@@ -1279,34 +1285,34 @@ mod test {
     fn test_type_coercion_rewrite() -> Result<()> {
         // gt
         let schema = Arc::new(DFSchema::from_unqualifed_fields(
-            vec![Field::new("a", DataType::Int64, true)].into(),
+            vec![LogicalField::new("a", LogicalType::Int64, true)].into(),
             std::collections::HashMap::new(),
         )?);
         let mut rewriter = TypeCoercionRewriter { schema: &schema };
         let expr = is_true(lit(12i32).gt(lit(13i64)));
-        let expected = is_true(cast(lit(12i32), DataType::Int64).gt(lit(13i64)));
+        let expected = is_true(cast(lit(12i32), LogicalType::Int64).gt(lit(13i64)));
         let result = expr.rewrite(&mut rewriter).data()?;
         assert_eq!(expected, result);
 
         // eq
         let schema = Arc::new(DFSchema::from_unqualifed_fields(
-            vec![Field::new("a", DataType::Int64, true)].into(),
+            vec![LogicalField::new("a", LogicalType::Int64, true)].into(),
             std::collections::HashMap::new(),
         )?);
         let mut rewriter = TypeCoercionRewriter { schema: &schema };
         let expr = is_true(lit(12i32).eq(lit(13i64)));
-        let expected = is_true(cast(lit(12i32), DataType::Int64).eq(lit(13i64)));
+        let expected = is_true(cast(lit(12i32), LogicalType::Int64).eq(lit(13i64)));
         let result = expr.rewrite(&mut rewriter).data()?;
         assert_eq!(expected, result);
 
         // lt
         let schema = Arc::new(DFSchema::from_unqualifed_fields(
-            vec![Field::new("a", DataType::Int64, true)].into(),
+            vec![LogicalField::new("a", LogicalType::Int64, true)].into(),
             std::collections::HashMap::new(),
         )?);
         let mut rewriter = TypeCoercionRewriter { schema: &schema };
         let expr = is_true(lit(12i32).lt(lit(13i64)));
-        let expected = is_true(cast(lit(12i32), DataType::Int64).lt(lit(13i64)));
+        let expected = is_true(cast(lit(12i32), LogicalType::Int64).lt(lit(13i64)));
         let result = expr.rewrite(&mut rewriter).data()?;
         assert_eq!(expected, result);
 
@@ -1317,9 +1323,9 @@ mod test {
     fn binary_op_date32_eq_ts() -> Result<()> {
         let expr = cast(
             lit("1998-03-18"),
-            DataType::Timestamp(TimeUnit::Nanosecond, None),
+            LogicalType::Timestamp(TimeUnit::Nanosecond, None),
         )
-        .eq(cast(lit("1998-03-18"), DataType::Date32));
+        .eq(cast(lit("1998-03-18"), LogicalType::Date32));
         let empty = empty();
         let plan = LogicalPlan::Projection(Projection::try_new(vec![expr], empty)?);
         dbg!(&plan);
@@ -1331,7 +1337,7 @@ mod test {
 
     fn cast_if_not_same_type(
         expr: Box<Expr>,
-        data_type: &DataType,
+        data_type: &LogicalType,
         schema: &DFSchemaRef,
     ) -> Box<Expr> {
         if &expr.get_type(schema).unwrap() != data_type {
@@ -1343,8 +1349,8 @@ mod test {
 
     fn cast_helper(
         case: Case,
-        case_when_type: DataType,
-        then_else_type: DataType,
+        case_when_type: LogicalType,
+        then_else_type: LogicalType,
         schema: &DFSchemaRef,
     ) -> Case {
         let expr = case
@@ -1375,23 +1381,23 @@ mod test {
     fn test_case_expression_coercion() -> Result<()> {
         let schema = Arc::new(DFSchema::from_unqualifed_fields(
             vec![
-                Field::new("boolean", DataType::Boolean, true),
-                Field::new("integer", DataType::Int32, true),
-                Field::new("float", DataType::Float32, true),
-                Field::new(
+                LogicalField::new("boolean", LogicalType::Boolean, true),
+                LogicalField::new("integer", LogicalType::Int32, true),
+                LogicalField::new("float", LogicalType::Float32, true),
+                LogicalField::new(
                     "timestamp",
-                    DataType::Timestamp(TimeUnit::Nanosecond, None),
+                    LogicalType::Timestamp(TimeUnit::Nanosecond, None),
                     true,
                 ),
-                Field::new("date", DataType::Date32, true),
-                Field::new(
+                LogicalField::new("date", LogicalType::Date32, true),
+                LogicalField::new(
                     "interval",
-                    DataType::Interval(arrow::datatypes::IntervalUnit::MonthDayNano),
+                    LogicalType::Interval(arrow::datatypes::IntervalUnit::MonthDayNano),
                     true,
                 ),
-                Field::new("binary", DataType::Binary, true),
-                Field::new("string", DataType::Utf8, true),
-                Field::new("decimal", DataType::Decimal128(10, 10), true),
+                LogicalField::new("binary", LogicalType::Binary, true),
+                LogicalField::new("string", LogicalType::Utf8, true),
+                LogicalField::new("decimal", LogicalType::Decimal128(10, 10), true),
             ]
             .into(),
             std::collections::HashMap::new(),
@@ -1406,8 +1412,8 @@ mod test {
             ],
             else_expr: None,
         };
-        let case_when_common_type = DataType::Boolean;
-        let then_else_common_type = DataType::Utf8;
+        let case_when_common_type = LogicalType::Boolean;
+        let then_else_common_type = LogicalType::Utf8;
         let expected = cast_helper(
             case.clone(),
             case_when_common_type,
@@ -1426,8 +1432,8 @@ mod test {
             ],
             else_expr: Some(Box::new(col("string"))),
         };
-        let case_when_common_type = DataType::Utf8;
-        let then_else_common_type = DataType::Utf8;
+        let case_when_common_type = LogicalType::Utf8;
+        let then_else_common_type = LogicalType::Utf8;
         let expected = cast_helper(
             case.clone(),
             case_when_common_type,
@@ -1484,7 +1490,7 @@ mod test {
             Operator::Plus,
             Box::new(cast(
                 lit("2000-01-01T00:00:00"),
-                DataType::Timestamp(TimeUnit::Nanosecond, None),
+                LogicalType::Timestamp(TimeUnit::Nanosecond, None),
             )),
         ));
         let empty = empty();
@@ -1499,12 +1505,12 @@ mod test {
         let expr = Expr::BinaryExpr(BinaryExpr::new(
             Box::new(cast(
                 lit("1998-03-18"),
-                DataType::Timestamp(TimeUnit::Nanosecond, None),
+                LogicalType::Timestamp(TimeUnit::Nanosecond, None),
             )),
             Operator::Minus,
             Box::new(cast(
                 lit("1998-03-18"),
-                DataType::Timestamp(TimeUnit::Nanosecond, None),
+                LogicalType::Timestamp(TimeUnit::Nanosecond, None),
             )),
         ));
         let empty = empty();
@@ -1518,8 +1524,8 @@ mod test {
 
     #[test]
     fn in_subquery_cast_subquery() -> Result<()> {
-        let empty_int32 = empty_with_type(DataType::Int32);
-        let empty_int64 = empty_with_type(DataType::Int64);
+        let empty_int32 = empty_with_type(LogicalType::Int32);
+        let empty_int64 = empty_with_type(LogicalType::Int64);
 
         let in_subquery_expr = Expr::InSubquery(InSubquery::new(
             Box::new(col("a")),
@@ -1543,8 +1549,8 @@ mod test {
 
     #[test]
     fn in_subquery_cast_expr() -> Result<()> {
-        let empty_int32 = empty_with_type(DataType::Int32);
-        let empty_int64 = empty_with_type(DataType::Int64);
+        let empty_int32 = empty_with_type(LogicalType::Int32);
+        let empty_int64 = empty_with_type(LogicalType::Int64);
 
         let in_subquery_expr = Expr::InSubquery(InSubquery::new(
             Box::new(col("a")),
@@ -1567,8 +1573,8 @@ mod test {
 
     #[test]
     fn in_subquery_cast_all() -> Result<()> {
-        let empty_inside = empty_with_type(DataType::Decimal128(10, 5));
-        let empty_outside = empty_with_type(DataType::Decimal128(8, 8));
+        let empty_inside = empty_with_type(LogicalType::Decimal128(10, 5));
+        let empty_outside = empty_with_type(LogicalType::Decimal128(8, 8));
 
         let in_subquery_expr = Expr::InSubquery(InSubquery::new(
             Box::new(col("a")),
diff --git a/datafusion/optimizer/src/common_subexpr_eliminate.rs b/datafusion/optimizer/src/common_subexpr_eliminate.rs
index e760845e043a..2958082108a2 100644
--- a/datafusion/optimizer/src/common_subexpr_eliminate.rs
+++ b/datafusion/optimizer/src/common_subexpr_eliminate.rs
@@ -1094,6 +1094,8 @@ mod test {
     use std::iter;
 
     use arrow::datatypes::{DataType, Field, Schema};
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::expr::AggregateFunction;
     use datafusion_expr::logical_plan::{table_scan, JoinType};
     use datafusion_expr::{
@@ -1644,9 +1646,9 @@ mod test {
         let plan = table_scan(Some("table"), &schema, None)
             .unwrap()
             .filter(
-                cast(col("a"), DataType::Int64)
+                cast(col("a"), LogicalType::Int64)
                     .lt(lit(1_i64))
-                    .and(cast(col("a"), DataType::Int64).not_eq(lit(1_i64))),
+                    .and(cast(col("a"), LogicalType::Int64).not_eq(lit(1_i64))),
             )
             .unwrap()
             .build()
@@ -1704,9 +1706,9 @@ mod test {
         let grouping = grouping_set(vec![vec![col("a"), col("b")], vec![col("c")]]);
         let schema = DFSchema::from_unqualifed_fields(
             vec![
-                Field::new("a", DataType::Int32, false),
-                Field::new("b", DataType::Int32, false),
-                Field::new("c", DataType::Int32, false),
+                LogicalField::new("a", LogicalType::Int32, false),
+                LogicalField::new("b", LogicalType::Int32, false),
+                LogicalField::new("c", LogicalType::Int32, false),
             ]
             .into(),
             HashMap::default(),
@@ -1723,8 +1725,8 @@ mod test {
         let grouping = grouping_set(vec![vec![col("a"), col("b")], vec![col("a")]]);
         let schema = DFSchema::from_unqualifed_fields(
             vec![
-                Field::new("a", DataType::Int32, false),
-                Field::new("b", DataType::Int32, false),
+                LogicalField::new("a", LogicalType::Int32, false),
+                LogicalField::new("b", LogicalType::Int32, false),
             ]
             .into(),
             HashMap::default(),
@@ -1791,7 +1793,7 @@ mod test {
     fn test_extract_expressions_from_col() -> Result<()> {
         let mut result = Vec::with_capacity(1);
         let schema = DFSchema::from_unqualifed_fields(
-            vec![Field::new("a", DataType::Int32, false)].into(),
+            vec![LogicalField::new("a", LogicalType::Int32, false)].into(),
             HashMap::default(),
         )?;
         extract_expressions(&col("a"), &schema, &mut result)?;
diff --git a/datafusion/optimizer/src/decorrelate_predicate_subquery.rs b/datafusion/optimizer/src/decorrelate_predicate_subquery.rs
index 81d6dc863af6..7f009cbd1164 100644
--- a/datafusion/optimizer/src/decorrelate_predicate_subquery.rs
+++ b/datafusion/optimizer/src/decorrelate_predicate_subquery.rs
@@ -369,7 +369,7 @@ mod tests {
     use super::*;
     use crate::test::*;
 
-    use arrow::datatypes::DataType;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::{and, binary_expr, col, lit, not, or, out_ref_col};
 
     fn assert_optimized_plan_equal(plan: LogicalPlan, expected: &str) -> Result<()> {
@@ -564,7 +564,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
                     col("orders.o_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
                 .build()?,
@@ -605,7 +605,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("lineitem"))
                 .filter(
                     col("lineitem.l_orderkey")
-                        .eq(out_ref_col(DataType::Int64, "orders.o_orderkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "orders.o_orderkey")),
                 )?
                 .project(vec![col("lineitem.l_orderkey")])?
                 .build()?,
@@ -616,7 +616,7 @@ mod tests {
                 .filter(
                     in_subquery(col("orders.o_orderkey"), lineitem).and(
                         col("orders.o_custkey")
-                            .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                            .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                     ),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -653,7 +653,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .and(col("o_orderkey").eq(lit(1))),
                 )?
@@ -688,8 +688,8 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
                 .build()?,
@@ -752,7 +752,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .not_eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -785,7 +785,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .lt(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -818,7 +818,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .or(col("o_orderkey").eq(lit(1))),
                 )?
@@ -876,7 +876,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -909,7 +909,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey").add(lit(1))])?
@@ -942,7 +942,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey"), col("orders.o_orderkey")])?
@@ -971,7 +971,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1008,7 +1008,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1045,7 +1045,7 @@ mod tests {
     fn in_subquery_correlated() -> Result<()> {
         let sq = Arc::new(
             LogicalPlanBuilder::from(test_table_scan_with_name("sq")?)
-                .filter(out_ref_col(DataType::UInt32, "test.a").eq(col("sq.a")))?
+                .filter(out_ref_col(LogicalType::UInt32, "test.a").eq(col("sq.a")))?
                 .project(vec![col("c")])?
                 .build()?,
         );
@@ -1203,7 +1203,7 @@ mod tests {
 
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
-                out_ref_col(DataType::UInt32, "test.a")
+                out_ref_col(LogicalType::UInt32, "test.a")
                     .eq(col("sq.a"))
                     .and(col("sq.a").add(lit(1u32)).eq(col("sq.b"))),
             )?
@@ -1238,8 +1238,8 @@ mod tests {
 
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
-                out_ref_col(DataType::UInt32, "test.a")
-                    .add(out_ref_col(DataType::UInt32, "test.b"))
+                out_ref_col(LogicalType::UInt32, "test.a")
+                    .add(out_ref_col(LogicalType::UInt32, "test.b"))
                     .eq(col("sq.a").add(col("sq.b")))
                     .and(col("sq.a").add(lit(1u32)).eq(col("sq.b"))),
             )?
@@ -1274,12 +1274,12 @@ mod tests {
         let subquery_scan2 = test_table_scan_with_name("sq2")?;
 
         let subquery1 = LogicalPlanBuilder::from(subquery_scan1)
-            .filter(out_ref_col(DataType::UInt32, "test.a").gt(col("sq1.a")))?
+            .filter(out_ref_col(LogicalType::UInt32, "test.a").gt(col("sq1.a")))?
             .project(vec![col("c") * lit(2u32)])?
             .build()?;
 
         let subquery2 = LogicalPlanBuilder::from(subquery_scan2)
-            .filter(out_ref_col(DataType::UInt32, "test.a").gt(col("sq2.a")))?
+            .filter(out_ref_col(LogicalType::UInt32, "test.a").gt(col("sq2.a")))?
             .project(vec![col("c") * lit(2u32)])?
             .build()?;
 
@@ -1351,7 +1351,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
                     col("orders.o_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
                 .build()?,
@@ -1382,7 +1382,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("lineitem"))
                 .filter(
                     col("lineitem.l_orderkey")
-                        .eq(out_ref_col(DataType::Int64, "orders.o_orderkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "orders.o_orderkey")),
                 )?
                 .project(vec![col("lineitem.l_orderkey")])?
                 .build()?,
@@ -1393,7 +1393,7 @@ mod tests {
                 .filter(
                     exists(lineitem).and(
                         col("orders.o_custkey")
-                            .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                            .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                     ),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1424,7 +1424,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .and(col("o_orderkey").eq(lit(1))),
                 )?
@@ -1452,7 +1452,7 @@ mod tests {
     fn exists_subquery_no_cols() -> Result<()> {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
-                .filter(out_ref_col(DataType::Int64, "customer.c_custkey").eq(lit(1u32)))?
+                .filter(out_ref_col(LogicalType::Int64, "customer.c_custkey").eq(lit(1u32)))?
                 .project(vec![col("orders.o_custkey")])?
                 .build()?,
         );
@@ -1497,7 +1497,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .not_eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1525,7 +1525,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .lt(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1553,7 +1553,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .or(col("o_orderkey").eq(lit(1))),
                 )?
@@ -1582,7 +1582,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .build()?,
@@ -1608,7 +1608,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey").add(lit(1))])?
@@ -1636,7 +1636,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .project(vec![col("orders.o_custkey")])?
@@ -1690,7 +1690,7 @@ mod tests {
     fn exists_subquery_correlated() -> Result<()> {
         let sq = Arc::new(
             LogicalPlanBuilder::from(test_table_scan_with_name("sq")?)
-                .filter(out_ref_col(DataType::UInt32, "test.a").eq(col("sq.a")))?
+                .filter(out_ref_col(LogicalType::UInt32, "test.a").eq(col("sq.a")))?
                 .project(vec![col("c")])?
                 .build()?,
         );
@@ -1741,12 +1741,12 @@ mod tests {
         let subquery_scan2 = test_table_scan_with_name("sq2")?;
 
         let subquery1 = LogicalPlanBuilder::from(subquery_scan1)
-            .filter(out_ref_col(DataType::UInt32, "test.a").eq(col("sq1.a")))?
+            .filter(out_ref_col(LogicalType::UInt32, "test.a").eq(col("sq1.a")))?
             .project(vec![col("c")])?
             .build()?;
 
         let subquery2 = LogicalPlanBuilder::from(subquery_scan2)
-            .filter(out_ref_col(DataType::UInt32, "test.a").eq(col("sq2.a")))?
+            .filter(out_ref_col(LogicalType::UInt32, "test.a").eq(col("sq2.a")))?
             .project(vec![col("c")])?
             .build()?;
 
@@ -1780,7 +1780,7 @@ mod tests {
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
                 (lit(1u32) + col("sq.a"))
-                    .gt(out_ref_col(DataType::UInt32, "test.a") * lit(2u32)),
+                    .gt(out_ref_col(LogicalType::UInt32, "test.a") * lit(2u32)),
             )?
             .project(vec![lit(1u32)])?
             .build()?;
@@ -1832,7 +1832,7 @@ mod tests {
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
                 (lit(1u32) + col("sq.a"))
-                    .gt(out_ref_col(DataType::UInt32, "test.a") * lit(2u32)),
+                    .gt(out_ref_col(LogicalType::UInt32, "test.a") * lit(2u32)),
             )?
             .project(vec![col("sq.c")])?
             .distinct()?
@@ -1860,7 +1860,7 @@ mod tests {
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
                 (lit(1u32) + col("sq.a"))
-                    .gt(out_ref_col(DataType::UInt32, "test.a") * lit(2u32)),
+                    .gt(out_ref_col(LogicalType::UInt32, "test.a") * lit(2u32)),
             )?
             .project(vec![col("sq.b") + col("sq.c")])?
             .distinct()?
@@ -1888,7 +1888,7 @@ mod tests {
         let subquery = LogicalPlanBuilder::from(subquery_scan)
             .filter(
                 (lit(1u32) + col("sq.a"))
-                    .gt(out_ref_col(DataType::UInt32, "test.a") * lit(2u32)),
+                    .gt(out_ref_col(LogicalType::UInt32, "test.a") * lit(2u32)),
             )?
             .project(vec![lit(1u32), col("sq.c")])?
             .distinct()?
diff --git a/datafusion/optimizer/src/eliminate_one_union.rs b/datafusion/optimizer/src/eliminate_one_union.rs
index edf6b72d7e17..d88491be1979 100644
--- a/datafusion/optimizer/src/eliminate_one_union.rs
+++ b/datafusion/optimizer/src/eliminate_one_union.rs
@@ -65,11 +65,12 @@ mod tests {
     use super::*;
     use crate::test::*;
     use arrow::datatypes::{DataType, Field, Schema};
-    use datafusion_common::ToDFSchema;
     use datafusion_expr::{
         expr_rewriter::coerce_plan_expr_for_schema, logical_plan::table_scan,
     };
     use std::sync::Arc;
+    use datafusion_common::logical_type::schema::LogicalSchema;
+    use datafusion_common::ToDFSchema;
 
     fn schema() -> Schema {
         Schema::new(vec![
@@ -108,7 +109,7 @@ mod tests {
     fn eliminate_one_union() -> Result<()> {
         let table_plan = coerce_plan_expr_for_schema(
             &table_scan(Some("table"), &schema(), None)?.build()?,
-            &schema().to_dfschema()?,
+            &LogicalSchema::from(schema()).to_dfschema()?,
         )?;
         let schema = table_plan.schema().clone();
         let single_union_plan = LogicalPlan::Union(Union {
diff --git a/datafusion/optimizer/src/eliminate_outer_join.rs b/datafusion/optimizer/src/eliminate_outer_join.rs
index ccc637a0eb01..882499cfa68b 100644
--- a/datafusion/optimizer/src/eliminate_outer_join.rs
+++ b/datafusion/optimizer/src/eliminate_outer_join.rs
@@ -301,7 +301,7 @@ fn extract_non_nullable_columns(
 mod tests {
     use super::*;
     use crate::test::*;
-    use arrow::datatypes::DataType;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::{
         binary_expr, cast, col, lit,
         logical_plan::builder::LogicalPlanBuilder,
@@ -427,9 +427,9 @@ mod tests {
                 None,
             )?
             .filter(binary_expr(
-                cast(col("t1.b"), DataType::Int64).gt(lit(10u32)),
+                cast(col("t1.b"), LogicalType::Int64).gt(lit(10u32)),
                 And,
-                try_cast(col("t2.c"), DataType::Int64).lt(lit(20u32)),
+                try_cast(col("t2.c"), LogicalType::Int64).lt(lit(20u32)),
             ))?
             .build()?;
         let expected = "\
diff --git a/datafusion/optimizer/src/extract_equijoin_predicate.rs b/datafusion/optimizer/src/extract_equijoin_predicate.rs
index 87d205139e8e..820ef149c347 100644
--- a/datafusion/optimizer/src/extract_equijoin_predicate.rs
+++ b/datafusion/optimizer/src/extract_equijoin_predicate.rs
@@ -156,11 +156,11 @@ fn split_eq_and_noneq_join_predicate(
 mod tests {
     use super::*;
     use crate::test::*;
-    use arrow::datatypes::DataType;
     use datafusion_expr::{
         col, lit, logical_plan::builder::LogicalPlanBuilder, JoinType,
     };
     use std::sync::Arc;
+    use datafusion_common::logical_type::LogicalType;
 
     fn assert_plan_eq(plan: LogicalPlan, expected: &str) -> Result<()> {
         assert_optimized_plan_eq_display_indent(
@@ -362,8 +362,8 @@ mod tests {
 
         // filter: t1.a + CAST(Int64(1), UInt32) = t2.a + CAST(Int64(2), UInt32) as t1.a + 1 = t2.a + 2
         let filter = Expr::eq(
-            col("t1.a") + lit(1i64).cast_to(&DataType::UInt32, &t1_schema)?,
-            col("t2.a") + lit(2i32).cast_to(&DataType::UInt32, &t2_schema)?,
+            col("t1.a") + lit(1i64).cast_to(&LogicalType::UInt32, &t1_schema)?,
+            col("t2.a") + lit(2i32).cast_to(&LogicalType::UInt32, &t2_schema)?,
         )
         .alias("t1.a + 1 = t2.a + 2");
         let plan = LogicalPlanBuilder::from(t1)
diff --git a/datafusion/optimizer/src/optimize_projections/mod.rs b/datafusion/optimizer/src/optimize_projections/mod.rs
index 2fbf77523bd1..e3d0bbf243c2 100644
--- a/datafusion/optimizer/src/optimize_projections/mod.rs
+++ b/datafusion/optimizer/src/optimize_projections/mod.rs
@@ -810,6 +810,8 @@ mod tests {
     use datafusion_common::{
         Column, DFSchema, DFSchemaRef, JoinType, Result, TableReference,
     };
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::AggregateExt;
     use datafusion_expr::{
         binary_expr, build_join_schema,
@@ -1172,7 +1174,7 @@ mod tests {
     fn test_try_cast() -> Result<()> {
         let table_scan = test_table_scan()?;
         let plan = LogicalPlanBuilder::from(table_scan)
-            .project(vec![try_cast(col("a"), DataType::Float64)])?
+            .project(vec![try_cast(col("a"), LogicalType::Float64)])?
             .build()?;
 
         let expected = "Projection: TRY_CAST(test.a AS Float64)\
@@ -1544,15 +1546,15 @@ mod tests {
                 vec![
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("a", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("a", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("b", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("b", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test2".into()),
-                        Arc::new(Field::new("c1", DataType::UInt32, true))
+                        Arc::new(LogicalField::new("c1", LogicalType::UInt32, true))
                     ),
                 ],
                 HashMap::new()
@@ -1596,15 +1598,15 @@ mod tests {
                 vec![
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("a", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("a", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("b", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("b", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test2".into()),
-                        Arc::new(Field::new("c1", DataType::UInt32, true))
+                        Arc::new(LogicalField::new("c1", LogicalType::UInt32, true))
                     ),
                 ],
                 HashMap::new()
@@ -1646,15 +1648,15 @@ mod tests {
                 vec![
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("a", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("a", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test".into()),
-                        Arc::new(Field::new("b", DataType::UInt32, false))
+                        Arc::new(LogicalField::new("b", LogicalType::UInt32, false))
                     ),
                     (
                         Some("test2".into()),
-                        Arc::new(Field::new("a", DataType::UInt32, true))
+                        Arc::new(LogicalField::new("a", LogicalType::UInt32, true))
                     ),
                 ],
                 HashMap::new()
@@ -1671,7 +1673,7 @@ mod tests {
         let projection = LogicalPlanBuilder::from(table_scan)
             .project(vec![Expr::Cast(Cast::new(
                 Box::new(col("c")),
-                DataType::Float64,
+                LogicalType::Float64,
             ))])?
             .build()?;
 
diff --git a/datafusion/optimizer/src/optimizer.rs b/datafusion/optimizer/src/optimizer.rs
index 14e5ac141eeb..37fd448eff43 100644
--- a/datafusion/optimizer/src/optimizer.rs
+++ b/datafusion/optimizer/src/optimizer.rs
@@ -540,17 +540,17 @@ mod tests {
             "Optimizer rule 'get table_scan rule' failed\n\
             caused by\nget table_scan rule\ncaused by\n\
             Internal error: Failed due to a difference in schemas, \
-            original schema: DFSchema { inner: Schema { \
+            original schema: DFSchema { inner: LogicalSchema { \
             fields: [], \
             metadata: {} }, \
             field_qualifiers: [], \
             functional_dependencies: FunctionalDependencies { deps: [] } \
             }, \
-            new schema: DFSchema { inner: Schema { \
+            new schema: DFSchema { inner: LogicalSchema { \
             fields: [\
-              Field { name: \"a\", data_type: UInt32, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, \
-              Field { name: \"b\", data_type: UInt32, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, \
-              Field { name: \"c\", data_type: UInt32, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }\
+              LogicalField { name: \"a\", data_type: UInt32, nullable: false, metadata: {} }, \
+              LogicalField { name: \"b\", data_type: UInt32, nullable: false, metadata: {} }, \
+              LogicalField { name: \"c\", data_type: UInt32, nullable: false, metadata: {} }\
             ], \
             metadata: {} }, \
             field_qualifiers: [Some(Bare { table: \"test\" }), Some(Bare { table: \"test\" }), Some(Bare { table: \"test\" })], \
diff --git a/datafusion/optimizer/src/propagate_empty_relation.rs b/datafusion/optimizer/src/propagate_empty_relation.rs
index 63b357510f2f..f8be9b965f9a 100644
--- a/datafusion/optimizer/src/propagate_empty_relation.rs
+++ b/datafusion/optimizer/src/propagate_empty_relation.rs
@@ -246,9 +246,10 @@ fn empty_child(plan: &LogicalPlan) -> Result<Option<LogicalPlan>> {
 mod tests {
     use std::sync::Arc;
 
-    use arrow::datatypes::{DataType, Field, Schema};
+    use arrow::datatypes::{DataType, Field, Fields, Schema};
 
     use datafusion_common::{Column, DFSchema, JoinType, ScalarValue};
+    use datafusion_common::logical_type::fields::LogicalFields;
     use datafusion_expr::logical_plan::table_scan;
     use datafusion_expr::{
         binary_expr, col, lit, logical_plan::builder::LogicalPlanBuilder, Expr, Operator,
@@ -574,7 +575,7 @@ mod tests {
     fn test_empty_with_non_empty() -> Result<()> {
         let table_scan = test_table_scan()?;
 
-        let fields = test_table_scan_fields();
+        let fields = LogicalFields::from(Fields::from(test_table_scan_fields()));
 
         let empty = LogicalPlan::EmptyRelation(EmptyRelation {
             produce_one_row: false,
diff --git a/datafusion/optimizer/src/push_down_filter.rs b/datafusion/optimizer/src/push_down_filter.rs
index fa432ad76de5..91edc6844313 100644
--- a/datafusion/optimizer/src/push_down_filter.rs
+++ b/datafusion/optimizer/src/push_down_filter.rs
@@ -1149,7 +1149,7 @@ mod tests {
 
     use arrow::datatypes::{DataType, Field, Schema, SchemaRef};
     use async_trait::async_trait;
-
+    use datafusion_common::logical_type::schema::LogicalSchema;
     use datafusion_common::ScalarValue;
     use datafusion_expr::expr::ScalarFunction;
     use datafusion_expr::logical_plan::table_scan;
@@ -2387,7 +2387,7 @@ mod tests {
             table_name: "test".into(),
             filters: vec![],
             projected_schema: Arc::new(DFSchema::try_from(
-                (*test_provider.schema()).clone(),
+               LogicalSchema::from((*test_provider.schema()).clone()),
             )?),
             projection: None,
             source: Arc::new(test_provider),
@@ -2459,7 +2459,7 @@ mod tests {
             table_name: "test".into(),
             filters: vec![col("a").eq(lit(10i64)), col("b").gt(lit(11i64))],
             projected_schema: Arc::new(DFSchema::try_from(
-                (*test_provider.schema()).clone(),
+                LogicalSchema::from((*test_provider.schema()).clone()),
             )?),
             projection: Some(vec![0]),
             source: Arc::new(test_provider),
@@ -2488,7 +2488,7 @@ mod tests {
             table_name: "test".into(),
             filters: vec![],
             projected_schema: Arc::new(DFSchema::try_from(
-                (*test_provider.schema()).clone(),
+                LogicalSchema::from((*test_provider.schema()).clone()),
             )?),
             projection: Some(vec![0]),
             source: Arc::new(test_provider),
diff --git a/datafusion/optimizer/src/scalar_subquery_to_join.rs b/datafusion/optimizer/src/scalar_subquery_to_join.rs
index 0333cc8dde36..b79343f9b041 100644
--- a/datafusion/optimizer/src/scalar_subquery_to_join.rs
+++ b/datafusion/optimizer/src/scalar_subquery_to_join.rs
@@ -392,7 +392,7 @@ mod tests {
     use super::*;
     use crate::test::*;
 
-    use arrow::datatypes::DataType;
+    use datafusion_common::logical_type::LogicalType;
     use datafusion_expr::test::function_stub::sum;
     use datafusion_expr::{col, lit, max, min, out_ref_col, scalar_subquery, Between};
 
@@ -403,7 +403,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
                     col("orders.o_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
                 .project(vec![max(col("orders.o_custkey"))])?
@@ -447,7 +447,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("lineitem"))
                 .filter(
                     col("lineitem.l_orderkey")
-                        .eq(out_ref_col(DataType::Int64, "orders.o_orderkey")),
+                        .eq(out_ref_col(LogicalType::Int64, "orders.o_orderkey")),
                 )?
                 .aggregate(
                     Vec::<Expr>::new(),
@@ -461,7 +461,7 @@ mod tests {
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
                     col("orders.o_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey"))
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey"))
                         .and(col("orders.o_totalprice").lt(scalar_subquery(lineitem))),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![sum(col("orders.o_totalprice"))])?
@@ -502,7 +502,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .and(col("o_orderkey").eq(lit(1))),
                 )?
@@ -540,8 +540,8 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
-                        .eq(out_ref_col(DataType::Int64, "customer.c_custkey")),
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
+                        .eq(out_ref_col(LogicalType::Int64, "customer.c_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
                 .project(vec![max(col("orders.o_custkey"))])?
@@ -610,7 +610,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .not_eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -637,7 +637,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .lt(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -664,7 +664,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey"))
                         .or(col("o_orderkey").eq(lit(1))),
                 )?
@@ -713,7 +713,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -775,7 +775,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -814,7 +814,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -854,7 +854,7 @@ mod tests {
         let sq = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
@@ -893,7 +893,7 @@ mod tests {
     fn exists_subquery_correlated() -> Result<()> {
         let sq = Arc::new(
             LogicalPlanBuilder::from(test_table_scan_with_name("sq")?)
-                .filter(out_ref_col(DataType::UInt32, "test.a").eq(col("sq.a")))?
+                .filter(out_ref_col(LogicalType::UInt32, "test.a").eq(col("sq.a")))?
                 .aggregate(Vec::<Expr>::new(), vec![min(col("c"))])?
                 .project(vec![min(col("c"))])?
                 .build()?,
@@ -989,7 +989,7 @@ mod tests {
         let sq1 = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![min(col("orders.o_custkey"))])?
@@ -999,7 +999,7 @@ mod tests {
         let sq2 = Arc::new(
             LogicalPlanBuilder::from(scan_tpch_table("orders"))
                 .filter(
-                    out_ref_col(DataType::Int64, "customer.c_custkey")
+                    out_ref_col(LogicalType::Int64, "customer.c_custkey")
                         .eq(col("orders.o_custkey")),
                 )?
                 .aggregate(Vec::<Expr>::new(), vec![max(col("orders.o_custkey"))])?
diff --git a/datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs b/datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs
index f2c80e4a7207..03c7c304b963 100644
--- a/datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs
+++ b/datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs
@@ -32,6 +32,7 @@ use datafusion_common::{
     tree_node::{Transformed, TransformedResult, TreeNode, TreeNodeRewriter},
 };
 use datafusion_common::{internal_err, DFSchema, DataFusionError, Result, ScalarValue};
+use datafusion_common::logical_type::extension::ExtensionType;
 use datafusion_expr::expr::{
     AggregateFunctionDefinition, InList, InSubquery, WindowFunction,
 };
@@ -1050,7 +1051,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&left, &right) && !info.nullable(&right)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_zero(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1061,7 +1062,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&right, &left) && !info.nullable(&left)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_zero(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1136,7 +1137,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&left, &right) && !info.nullable(&right)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_negative_one(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1147,7 +1148,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&right, &left) && !info.nullable(&left)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_negative_one(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1222,7 +1223,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&left, &right) && !info.nullable(&right)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_negative_one(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1233,7 +1234,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
                 right,
             }) if is_negative_of(&right, &left) && !info.nullable(&left)? => {
                 Transformed::yes(Expr::Literal(ScalarValue::new_negative_one(
-                    &info.get_data_type(&left)?,
+                    &info.get_data_type(&left)?.physical_type(),
                 )?))
             }
 
@@ -1245,7 +1246,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
             }) if expr_contains(&left, &right, BitwiseXor) => {
                 let expr = delete_xor_in_complex_expr(&left, &right, false);
                 Transformed::yes(if expr == *right {
-                    Expr::Literal(ScalarValue::new_zero(&info.get_data_type(&right)?)?)
+                    Expr::Literal(ScalarValue::new_zero(&info.get_data_type(&right)?.physical_type())?)
                 } else {
                     expr
                 })
@@ -1259,7 +1260,7 @@ impl<'a, S: SimplifyInfo> TreeNodeRewriter for Simplifier<'a, S> {
             }) if expr_contains(&right, &left, BitwiseXor) => {
                 let expr = delete_xor_in_complex_expr(&right, &left, true);
                 Transformed::yes(if expr == *left {
-                    Expr::Literal(ScalarValue::new_zero(&info.get_data_type(&left)?)?)
+                    Expr::Literal(ScalarValue::new_zero(&info.get_data_type(&left)?.physical_type())?)
                 } else {
                     expr
                 })
@@ -1783,7 +1784,9 @@ mod tests {
         ops::{BitAnd, BitOr, BitXor},
         sync::Arc,
     };
-
+    use datafusion_common::logical_type::field::LogicalField;
+    use datafusion_common::logical_type::LogicalType;
+    use datafusion_common::logical_type::schema::LogicalSchema;
     use crate::simplify_expressions::SimplifyContext;
     use crate::test::test_table_scan_with_name;
 
@@ -1822,9 +1825,9 @@ mod tests {
     }
 
     fn test_schema() -> DFSchemaRef {
-        Schema::new(vec![
-            Field::new("i", DataType::Int64, false),
-            Field::new("b", DataType::Boolean, true),
+        LogicalSchema::new(vec![
+            LogicalField::new("i", LogicalType::Int64, false),
+            LogicalField::new("b", LogicalType::Boolean, true),
         ])
         .to_dfschema_ref()
         .unwrap()
@@ -3007,14 +3010,14 @@ mod tests {
         Arc::new(
             DFSchema::from_unqualifed_fields(
                 vec![
-                    Field::new("c1", DataType::Utf8, true),
-                    Field::new("c2", DataType::Boolean, true),
-                    Field::new("c3", DataType::Int64, true),
-                    Field::new("c4", DataType::UInt32, true),
-                    Field::new("c1_non_null", DataType::Utf8, false),
-                    Field::new("c2_non_null", DataType::Boolean, false),
-                    Field::new("c3_non_null", DataType::Int64, false),
-                    Field::new("c4_non_null", DataType::UInt32, false),
+                    LogicalField::new("c1", LogicalType::Utf8, true),
+                    LogicalField::new("c2", LogicalType::Boolean, true),
+                    LogicalField::new("c3", LogicalType::Int64, true),
+                    LogicalField::new("c4", LogicalType::UInt32, true),
+                    LogicalField::new("c1_non_null", LogicalType::Utf8, false),
+                    LogicalField::new("c2_non_null", LogicalType::Boolean, false),
+                    LogicalField::new("c3_non_null", LogicalType::Int64, false),
+                    LogicalField::new("c4_non_null", LogicalType::UInt32, false),
                 ]
                 .into(),
                 HashMap::new(),
@@ -3102,7 +3105,7 @@ mod tests {
     #[test]
     fn simplify_expr_eq() {
         let schema = expr_test_schema();
-        assert_eq!(col("c2").get_type(&schema).unwrap(), DataType::Boolean);
+        assert_eq!(col("c2").get_type(&schema).unwrap(), LogicalType::Boolean);
 
         // true = true -> true
         assert_eq!(simplify(lit(true).eq(lit(true))), lit(true));
@@ -3126,7 +3129,7 @@ mod tests {
         // expression to non-boolean.
         //
         // Make sure c1 column to be used in tests is not boolean type
-        assert_eq!(col("c1").get_type(&schema).unwrap(), DataType::Utf8);
+        assert_eq!(col("c1").get_type(&schema).unwrap(), LogicalType::Utf8);
 
         // don't fold c1 = foo
         assert_eq!(simplify(col("c1").eq(lit("foo"))), col("c1").eq(lit("foo")),);
@@ -3136,7 +3139,7 @@ mod tests {
     fn simplify_expr_not_eq() {
         let schema = expr_test_schema();
 
-        assert_eq!(col("c2").get_type(&schema).unwrap(), DataType::Boolean);
+        assert_eq!(col("c2").get_type(&schema).unwrap(), LogicalType::Boolean);
 
         // c2 != true -> !c2
         assert_eq!(simplify(col("c2").not_eq(lit(true))), col("c2").not(),);
@@ -3157,7 +3160,7 @@ mod tests {
         // when one of the operand is not of boolean type, folding the
         // other boolean constant will change return type of
         // expression to non-boolean.
-        assert_eq!(col("c1").get_type(&schema).unwrap(), DataType::Utf8);
+        assert_eq!(col("c1").get_type(&schema).unwrap(), LogicalType::Utf8);
 
         assert_eq!(
             simplify(col("c1").not_eq(lit("foo"))),
diff --git a/datafusion/optimizer/src/simplify_expressions/simplify_exprs.rs b/datafusion/optimizer/src/simplify_expressions/simplify_exprs.rs
index e650d4c09c23..628da80bb3dd 100644
--- a/datafusion/optimizer/src/simplify_expressions/simplify_exprs.rs
+++ b/datafusion/optimizer/src/simplify_expressions/simplify_exprs.rs
@@ -93,7 +93,7 @@ impl SimplifyExpressions {
             // projection applied for simplification
             Arc::new(DFSchema::try_from_qualified_schema(
                 scan.table_name.clone(),
-                &scan.source.schema(),
+                &scan.source.schema().as_ref().clone().into(),
             )?)
         } else {
             Arc::new(DFSchema::empty())
@@ -151,7 +151,7 @@ mod tests {
 
     use arrow::datatypes::{DataType, Field, Schema};
     use chrono::{DateTime, Utc};
-
+    use datafusion_common::logical_type::LogicalType;
     use crate::optimizer::Optimizer;
     use datafusion_expr::logical_plan::builder::table_scan_with_filters;
     use datafusion_expr::logical_plan::table_scan;
@@ -445,7 +445,7 @@ mod tests {
     #[test]
     fn cast_expr() -> Result<()> {
         let table_scan = test_table_scan();
-        let proj = vec![Expr::Cast(Cast::new(Box::new(lit("0")), DataType::Int32))];
+        let proj = vec![Expr::Cast(Cast::new(Box::new(lit("0")), LogicalType::Int32))];
         let plan = LogicalPlanBuilder::from(table_scan)
             .project(proj)?
             .build()?;
@@ -703,9 +703,9 @@ mod tests {
         let t1 = test_table_scan_with_name("t1")?;
         let t2 = test_table_scan_with_name("t2")?;
 
-        let left_key = col("t1.a") + lit(1i64).cast_to(&DataType::UInt32, t1.schema())?;
+        let left_key = col("t1.a") + lit(1i64).cast_to(&LogicalType::UInt32, t1.schema())?;
         let right_key =
-            col("t2.a") + lit(2i64).cast_to(&DataType::UInt32, t2.schema())?;
+            col("t2.a") + lit(2i64).cast_to(&LogicalType::UInt32, t2.schema())?;
         let plan = LogicalPlanBuilder::from(t1)
             .join_with_expr_keys(
                 t2,
diff --git a/datafusion/optimizer/src/test/mod.rs b/datafusion/optimizer/src/test/mod.rs
index 2c7e8644026e..dbabdb5c926f 100644
--- a/datafusion/optimizer/src/test/mod.rs
+++ b/datafusion/optimizer/src/test/mod.rs
@@ -59,7 +59,7 @@ pub fn assert_fields_eq(plan: &LogicalPlan, expected: Vec<&str>) {
         .schema()
         .fields()
         .iter()
-        .map(|f| f.name().clone())
+        .map(|f| f.name().to_string())
         .collect();
     assert_eq!(actual, expected);
 }
diff --git a/datafusion/optimizer/src/unwrap_cast_in_comparison.rs b/datafusion/optimizer/src/unwrap_cast_in_comparison.rs
index fb18518fd226..0e19bf65e419 100644
--- a/datafusion/optimizer/src/unwrap_cast_in_comparison.rs
+++ b/datafusion/optimizer/src/unwrap_cast_in_comparison.rs
@@ -26,11 +26,12 @@ use crate::{OptimizerConfig, OptimizerRule};
 
 use crate::utils::NamePreserver;
 use arrow::datatypes::{
-    DataType, TimeUnit, MAX_DECIMAL_FOR_EACH_PRECISION, MIN_DECIMAL_FOR_EACH_PRECISION,
+    TimeUnit, MAX_DECIMAL_FOR_EACH_PRECISION, MIN_DECIMAL_FOR_EACH_PRECISION,
 };
 use arrow::temporal_conversions::{MICROSECONDS, MILLISECONDS, NANOSECONDS};
 use datafusion_common::tree_node::{Transformed, TreeNode, TreeNodeRewriter};
 use datafusion_common::{internal_err, DFSchema, DFSchemaRef, Result, ScalarValue};
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::expr::{BinaryExpr, Cast, InList, TryCast};
 use datafusion_expr::utils::merge_schema;
 use datafusion_expr::{lit, Expr, ExprSchemable, LogicalPlan, Operator};
@@ -104,7 +105,7 @@ impl OptimizerRule for UnwrapCastInComparison {
         if let LogicalPlan::TableScan(ts) = &plan {
             let source_schema = DFSchema::try_from_qualified_schema(
                 ts.table_name.clone(),
-                &ts.source.schema(),
+                &ts.source.schema().as_ref().clone().into(),
             )?;
             schema.merge(&source_schema);
         }
@@ -275,46 +276,39 @@ fn is_comparison_op(op: &Operator) -> bool {
 }
 
 /// Returns true if [UnwrapCastExprRewriter] supports this data type
-fn is_supported_type(data_type: &DataType) -> bool {
+fn is_supported_type(data_type: &LogicalType) -> bool {
     is_supported_numeric_type(data_type)
         || is_supported_string_type(data_type)
-        || is_supported_dictionary_type(data_type)
 }
 
 /// Returns true if [[UnwrapCastExprRewriter]] suppors this numeric type
-fn is_supported_numeric_type(data_type: &DataType) -> bool {
+fn is_supported_numeric_type(data_type: &LogicalType) -> bool {
     matches!(
         data_type,
-        DataType::UInt8
-            | DataType::UInt16
-            | DataType::UInt32
-            | DataType::UInt64
-            | DataType::Int8
-            | DataType::Int16
-            | DataType::Int32
-            | DataType::Int64
-            | DataType::Decimal128(_, _)
-            | DataType::Timestamp(_, _)
+        LogicalType::UInt8
+            | LogicalType::UInt16
+            | LogicalType::UInt32
+            | LogicalType::UInt64
+            | LogicalType::Int8
+            | LogicalType::Int16
+            | LogicalType::Int32
+            | LogicalType::Int64
+            | LogicalType::Decimal128(_, _)
+            | LogicalType::Timestamp(_, _)
     )
 }
 
 /// Returns true if [UnwrapCastExprRewriter] supports casting this value as a string
-fn is_supported_string_type(data_type: &DataType) -> bool {
-    matches!(data_type, DataType::Utf8 | DataType::LargeUtf8)
-}
-
-/// Returns true if [UnwrapCastExprRewriter] supports casting this value as a dictionary
-fn is_supported_dictionary_type(data_type: &DataType) -> bool {
-    matches!(data_type,
-                    DataType::Dictionary(_, inner) if is_supported_type(inner))
+fn is_supported_string_type(data_type: &LogicalType) -> bool {
+    matches!(data_type, LogicalType::Utf8 | LogicalType::LargeUtf8)
 }
 
 /// Convert a literal value from one data type to another
 fn try_cast_literal_to_type(
     lit_value: &ScalarValue,
-    target_type: &DataType,
+    target_type: &LogicalType,
 ) -> Option<ScalarValue> {
-    let lit_data_type = lit_value.data_type();
+    let lit_data_type = lit_value.data_type().into();
     if !is_supported_type(&lit_data_type) || !is_supported_type(target_type) {
         return None;
     }
@@ -324,15 +318,14 @@ fn try_cast_literal_to_type(
     }
     try_cast_numeric_literal(lit_value, target_type)
         .or_else(|| try_cast_string_literal(lit_value, target_type))
-        .or_else(|| try_cast_dictionary(lit_value, target_type))
 }
 
 /// Convert a numeric value from one numeric data type to another
 fn try_cast_numeric_literal(
     lit_value: &ScalarValue,
-    target_type: &DataType,
+    target_type: &LogicalType,
 ) -> Option<ScalarValue> {
-    let lit_data_type = lit_value.data_type();
+    let lit_data_type = lit_value.data_type().into();
     if !is_supported_numeric_type(&lit_data_type)
         || !is_supported_numeric_type(target_type)
     {
@@ -340,29 +333,29 @@ fn try_cast_numeric_literal(
     }
 
     let mul = match target_type {
-        DataType::UInt8
-        | DataType::UInt16
-        | DataType::UInt32
-        | DataType::UInt64
-        | DataType::Int8
-        | DataType::Int16
-        | DataType::Int32
-        | DataType::Int64 => 1_i128,
-        DataType::Timestamp(_, _) => 1_i128,
-        DataType::Decimal128(_, scale) => 10_i128.pow(*scale as u32),
+        LogicalType::UInt8
+        | LogicalType::UInt16
+        | LogicalType::UInt32
+        | LogicalType::UInt64
+        | LogicalType::Int8
+        | LogicalType::Int16
+        | LogicalType::Int32
+        | LogicalType::Int64 => 1_i128,
+        LogicalType::Timestamp(_, _) => 1_i128,
+        LogicalType::Decimal128(_, scale) => 10_i128.pow(*scale as u32),
         _ => return None,
     };
     let (target_min, target_max) = match target_type {
-        DataType::UInt8 => (u8::MIN as i128, u8::MAX as i128),
-        DataType::UInt16 => (u16::MIN as i128, u16::MAX as i128),
-        DataType::UInt32 => (u32::MIN as i128, u32::MAX as i128),
-        DataType::UInt64 => (u64::MIN as i128, u64::MAX as i128),
-        DataType::Int8 => (i8::MIN as i128, i8::MAX as i128),
-        DataType::Int16 => (i16::MIN as i128, i16::MAX as i128),
-        DataType::Int32 => (i32::MIN as i128, i32::MAX as i128),
-        DataType::Int64 => (i64::MIN as i128, i64::MAX as i128),
-        DataType::Timestamp(_, _) => (i64::MIN as i128, i64::MAX as i128),
-        DataType::Decimal128(precision, _) => (
+        LogicalType::UInt8 => (u8::MIN as i128, u8::MAX as i128),
+        LogicalType::UInt16 => (u16::MIN as i128, u16::MAX as i128),
+        LogicalType::UInt32 => (u32::MIN as i128, u32::MAX as i128),
+        LogicalType::UInt64 => (u64::MIN as i128, u64::MAX as i128),
+        LogicalType::Int8 => (i8::MIN as i128, i8::MAX as i128),
+        LogicalType::Int16 => (i16::MIN as i128, i16::MAX as i128),
+        LogicalType::Int32 => (i32::MIN as i128, i32::MAX as i128),
+        LogicalType::Int64 => (i64::MIN as i128, i64::MAX as i128),
+        LogicalType::Timestamp(_, _) => (i64::MIN as i128, i64::MAX as i128),
+        LogicalType::Decimal128(precision, _) => (
             // Different precision for decimal128 can store different range of value.
             // For example, the precision is 3, the max of value is `999` and the min
             // value is `-999`
@@ -413,47 +406,47 @@ fn try_cast_numeric_literal(
                 // the value casted from lit to the target type is in the range of target type.
                 // return the target type of scalar value
                 let result_scalar = match target_type {
-                    DataType::Int8 => ScalarValue::Int8(Some(value as i8)),
-                    DataType::Int16 => ScalarValue::Int16(Some(value as i16)),
-                    DataType::Int32 => ScalarValue::Int32(Some(value as i32)),
-                    DataType::Int64 => ScalarValue::Int64(Some(value as i64)),
-                    DataType::UInt8 => ScalarValue::UInt8(Some(value as u8)),
-                    DataType::UInt16 => ScalarValue::UInt16(Some(value as u16)),
-                    DataType::UInt32 => ScalarValue::UInt32(Some(value as u32)),
-                    DataType::UInt64 => ScalarValue::UInt64(Some(value as u64)),
-                    DataType::Timestamp(TimeUnit::Second, tz) => {
+                    LogicalType::Int8 => ScalarValue::Int8(Some(value as i8)),
+                    LogicalType::Int16 => ScalarValue::Int16(Some(value as i16)),
+                    LogicalType::Int32 => ScalarValue::Int32(Some(value as i32)),
+                    LogicalType::Int64 => ScalarValue::Int64(Some(value as i64)),
+                    LogicalType::UInt8 => ScalarValue::UInt8(Some(value as u8)),
+                    LogicalType::UInt16 => ScalarValue::UInt16(Some(value as u16)),
+                    LogicalType::UInt32 => ScalarValue::UInt32(Some(value as u32)),
+                    LogicalType::UInt64 => ScalarValue::UInt64(Some(value as u64)),
+                    LogicalType::Timestamp(TimeUnit::Second, tz) => {
                         let value = cast_between_timestamp(
                             lit_data_type,
-                            DataType::Timestamp(TimeUnit::Second, tz.clone()),
+                            LogicalType::Timestamp(TimeUnit::Second, tz.clone()),
                             value,
                         );
                         ScalarValue::TimestampSecond(value, tz.clone())
                     }
-                    DataType::Timestamp(TimeUnit::Millisecond, tz) => {
+                    LogicalType::Timestamp(TimeUnit::Millisecond, tz) => {
                         let value = cast_between_timestamp(
                             lit_data_type,
-                            DataType::Timestamp(TimeUnit::Millisecond, tz.clone()),
+                            LogicalType::Timestamp(TimeUnit::Millisecond, tz.clone()),
                             value,
                         );
                         ScalarValue::TimestampMillisecond(value, tz.clone())
                     }
-                    DataType::Timestamp(TimeUnit::Microsecond, tz) => {
+                    LogicalType::Timestamp(TimeUnit::Microsecond, tz) => {
                         let value = cast_between_timestamp(
                             lit_data_type,
-                            DataType::Timestamp(TimeUnit::Microsecond, tz.clone()),
+                            LogicalType::Timestamp(TimeUnit::Microsecond, tz.clone()),
                             value,
                         );
                         ScalarValue::TimestampMicrosecond(value, tz.clone())
                     }
-                    DataType::Timestamp(TimeUnit::Nanosecond, tz) => {
+                    LogicalType::Timestamp(TimeUnit::Nanosecond, tz) => {
                         let value = cast_between_timestamp(
                             lit_data_type,
-                            DataType::Timestamp(TimeUnit::Nanosecond, tz.clone()),
+                            LogicalType::Timestamp(TimeUnit::Nanosecond, tz.clone()),
                             value,
                         );
                         ScalarValue::TimestampNanosecond(value, tz.clone())
                     }
-                    DataType::Decimal128(p, s) => {
+                    LogicalType::Decimal128(p, s) => {
                         ScalarValue::Decimal128(Some(value), *p, *s)
                     }
                     _ => {
@@ -470,62 +463,36 @@ fn try_cast_numeric_literal(
 
 fn try_cast_string_literal(
     lit_value: &ScalarValue,
-    target_type: &DataType,
+    target_type: &LogicalType,
 ) -> Option<ScalarValue> {
     let string_value = match lit_value {
         ScalarValue::Utf8(s) | ScalarValue::LargeUtf8(s) => s.clone(),
         _ => return None,
     };
     let scalar_value = match target_type {
-        DataType::Utf8 => ScalarValue::Utf8(string_value),
-        DataType::LargeUtf8 => ScalarValue::LargeUtf8(string_value),
+        LogicalType::Utf8 => ScalarValue::Utf8(string_value),
+        LogicalType::LargeUtf8 => ScalarValue::LargeUtf8(string_value),
         _ => return None,
     };
     Some(scalar_value)
 }
 
-/// Attempt to cast to/from a dictionary type by wrapping/unwrapping the dictionary
-fn try_cast_dictionary(
-    lit_value: &ScalarValue,
-    target_type: &DataType,
-) -> Option<ScalarValue> {
-    let lit_value_type = lit_value.data_type();
-    let result_scalar = match (lit_value, target_type) {
-        // Unwrap dictionary when inner type matches target type
-        (ScalarValue::Dictionary(_, inner_value), _)
-            if inner_value.data_type() == *target_type =>
-        {
-            (**inner_value).clone()
-        }
-        // Wrap type when target type is dictionary
-        (_, DataType::Dictionary(index_type, inner_type))
-            if **inner_type == lit_value_type =>
-        {
-            ScalarValue::Dictionary(index_type.clone(), Box::new(lit_value.clone()))
-        }
-        _ => {
-            return None;
-        }
-    };
-    Some(result_scalar)
-}
-
 /// Cast a timestamp value from one unit to another
-fn cast_between_timestamp(from: DataType, to: DataType, value: i128) -> Option<i64> {
+fn cast_between_timestamp(from: LogicalType, to: LogicalType, value: i128) -> Option<i64> {
     let value = value as i64;
     let from_scale = match from {
-        DataType::Timestamp(TimeUnit::Second, _) => 1,
-        DataType::Timestamp(TimeUnit::Millisecond, _) => MILLISECONDS,
-        DataType::Timestamp(TimeUnit::Microsecond, _) => MICROSECONDS,
-        DataType::Timestamp(TimeUnit::Nanosecond, _) => NANOSECONDS,
+        LogicalType::Timestamp(TimeUnit::Second, _) => 1,
+        LogicalType::Timestamp(TimeUnit::Millisecond, _) => MILLISECONDS,
+        LogicalType::Timestamp(TimeUnit::Microsecond, _) => MICROSECONDS,
+        LogicalType::Timestamp(TimeUnit::Nanosecond, _) => NANOSECONDS,
         _ => return Some(value),
     };
 
     let to_scale = match to {
-        DataType::Timestamp(TimeUnit::Second, _) => 1,
-        DataType::Timestamp(TimeUnit::Millisecond, _) => MILLISECONDS,
-        DataType::Timestamp(TimeUnit::Microsecond, _) => MICROSECONDS,
-        DataType::Timestamp(TimeUnit::Nanosecond, _) => NANOSECONDS,
+        LogicalType::Timestamp(TimeUnit::Second, _) => 1,
+        LogicalType::Timestamp(TimeUnit::Millisecond, _) => MILLISECONDS,
+        LogicalType::Timestamp(TimeUnit::Microsecond, _) => MICROSECONDS,
+        LogicalType::Timestamp(TimeUnit::Nanosecond, _) => NANOSECONDS,
         _ => return Some(value),
     };
 
@@ -543,7 +510,8 @@ mod tests {
     use super::*;
 
     use arrow::compute::{cast_with_options, CastOptions};
-    use arrow::datatypes::Field;
+    use datafusion_common::logical_type::extension::ExtensionType;
+    use datafusion_common::logical_type::field::LogicalField;
     use datafusion_common::tree_node::TransformedResult;
     use datafusion_expr::{cast, col, in_list, try_cast};
 
@@ -551,7 +519,7 @@ mod tests {
     fn test_not_unwrap_cast_comparison() {
         let schema = expr_test_schema();
         // cast(INT32(c1), INT64) > INT64(c2)
-        let c1_gt_c2 = cast(col("c1"), DataType::Int64).gt(col("c2"));
+        let c1_gt_c2 = cast(col("c1"), LogicalType::Int64).gt(col("c2"));
         assert_eq!(optimize_test(c1_gt_c2.clone(), &schema), c1_gt_c2);
 
         // INT32(c1) < INT32(16), the type is same
@@ -559,7 +527,7 @@ mod tests {
         assert_eq!(optimize_test(expr_lt.clone(), &schema), expr_lt);
 
         // the 99999999999 is not within the range of MAX(int32) and MIN(int32), we don't cast the lit(99999999999) to int32 type
-        let expr_lt = cast(col("c1"), DataType::Int64).lt(lit(99999999999i64));
+        let expr_lt = cast(col("c1"), LogicalType::Int64).lt(lit(99999999999i64));
         assert_eq!(optimize_test(expr_lt.clone(), &schema), expr_lt);
     }
 
@@ -568,25 +536,25 @@ mod tests {
         let schema = expr_test_schema();
         // cast(c1, INT64) < INT64(16) -> INT32(c1) < cast(INT32(16))
         // the 16 is within the range of MAX(int32) and MIN(int32), we can cast the 16 to int32(16)
-        let expr_lt = cast(col("c1"), DataType::Int64).lt(lit(16i64));
+        let expr_lt = cast(col("c1"), LogicalType::Int64).lt(lit(16i64));
         let expected = col("c1").lt(lit(16i32));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
-        let expr_lt = try_cast(col("c1"), DataType::Int64).lt(lit(16i64));
+        let expr_lt = try_cast(col("c1"), LogicalType::Int64).lt(lit(16i64));
         let expected = col("c1").lt(lit(16i32));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // cast(c2, INT32) = INT32(16) => INT64(c2) = INT64(16)
-        let c2_eq_lit = cast(col("c2"), DataType::Int32).eq(lit(16i32));
+        let c2_eq_lit = cast(col("c2"), LogicalType::Int32).eq(lit(16i32));
         let expected = col("c2").eq(lit(16i64));
         assert_eq!(optimize_test(c2_eq_lit, &schema), expected);
 
         // cast(c1, INT64) < INT64(NULL) => INT32(c1) < INT32(NULL)
-        let c1_lt_lit_null = cast(col("c1"), DataType::Int64).lt(null_i64());
+        let c1_lt_lit_null = cast(col("c1"), LogicalType::Int64).lt(null_i64());
         let expected = col("c1").lt(null_i32());
         assert_eq!(optimize_test(c1_lt_lit_null, &schema), expected);
 
         // cast(INT8(NULL), INT32) < INT32(12) => INT8(NULL) < INT8(12)
-        let lit_lt_lit = cast(null_i8(), DataType::Int32).lt(lit(12i32));
+        let lit_lt_lit = cast(null_i8(), LogicalType::Int32).lt(lit(12i32));
         let expected = null_i8().lt(lit(12i8));
         assert_eq!(optimize_test(lit_lt_lit, &schema), expected);
     }
@@ -595,77 +563,38 @@ mod tests {
     fn test_unwrap_cast_comparison_unsigned() {
         // "cast(c6, UINT64) = 0u64 => c6 = 0u32
         let schema = expr_test_schema();
-        let expr_input = cast(col("c6"), DataType::UInt64).eq(lit(0u64));
+        let expr_input = cast(col("c6"), LogicalType::UInt64).eq(lit(0u64));
         let expected = col("c6").eq(lit(0u32));
         assert_eq!(optimize_test(expr_input, &schema), expected);
     }
 
-    #[test]
-    fn test_unwrap_cast_comparison_string() {
-        let schema = expr_test_schema();
-        let dict = ScalarValue::Dictionary(
-            Box::new(DataType::Int32),
-            Box::new(ScalarValue::from("value")),
-        );
-
-        // cast(str1 as Dictionary<Int32, Utf8>) = arrow_cast('value', 'Dictionary<Int32, Utf8>') => str1 = Utf8('value1')
-        let expr_input = cast(col("str1"), dict.data_type()).eq(lit(dict.clone()));
-        let expected = col("str1").eq(lit("value"));
-        assert_eq!(optimize_test(expr_input, &schema), expected);
-
-        // cast(tag as Utf8) = Utf8('value') => tag = arrow_cast('value', 'Dictionary<Int32, Utf8>')
-        let expr_input = cast(col("tag"), DataType::Utf8).eq(lit("value"));
-        let expected = col("tag").eq(lit(dict.clone()));
-        assert_eq!(optimize_test(expr_input, &schema), expected);
-
-        // Verify reversed argument order
-        // arrow_cast('value', 'Dictionary<Int32, Utf8>') = cast(str1 as Dictionary<Int32, Utf8>) => Utf8('value1') = str1
-        let expr_input = lit(dict.clone()).eq(cast(col("str1"), dict.data_type()));
-        let expected = lit("value").eq(col("str1"));
-        assert_eq!(optimize_test(expr_input, &schema), expected);
-    }
-
-    #[test]
-    fn test_unwrap_cast_comparison_large_string() {
-        let schema = expr_test_schema();
-        // cast(largestr as Dictionary<Int32, LargeUtf8>) = arrow_cast('value', 'Dictionary<Int32, LargeUtf8>') => str1 = LargeUtf8('value1')
-        let dict = ScalarValue::Dictionary(
-            Box::new(DataType::Int32),
-            Box::new(ScalarValue::LargeUtf8(Some("value".to_owned()))),
-        );
-        let expr_input = cast(col("largestr"), dict.data_type()).eq(lit(dict.clone()));
-        let expected =
-            col("largestr").eq(lit(ScalarValue::LargeUtf8(Some("value".to_owned()))));
-        assert_eq!(optimize_test(expr_input, &schema), expected);
-    }
-
     #[test]
     fn test_not_unwrap_cast_with_decimal_comparison() {
         let schema = expr_test_schema();
         // integer to decimal: value is out of the bounds of the decimal
         // cast(c3, INT64) = INT64(100000000000000000)
-        let expr_eq = cast(col("c3"), DataType::Int64).eq(lit(100000000000000000i64));
+        let expr_eq = cast(col("c3"), LogicalType::Int64).eq(lit(100000000000000000i64));
         assert_eq!(optimize_test(expr_eq.clone(), &schema), expr_eq);
 
         // cast(c4, INT64) = INT64(1000) will overflow the i128
-        let expr_eq = cast(col("c4"), DataType::Int64).eq(lit(1000i64));
+        let expr_eq = cast(col("c4"), LogicalType::Int64).eq(lit(1000i64));
         assert_eq!(optimize_test(expr_eq.clone(), &schema), expr_eq);
 
         // decimal to decimal: value will lose the scale when convert to the target data type
         // c3 = DECIMAL(12340,20,4)
         let expr_eq =
-            cast(col("c3"), DataType::Decimal128(20, 4)).eq(lit_decimal(12340, 20, 4));
+            cast(col("c3"), LogicalType::Decimal128(20, 4)).eq(lit_decimal(12340, 20, 4));
         assert_eq!(optimize_test(expr_eq.clone(), &schema), expr_eq);
 
         // decimal to integer
         // c1 = DECIMAL(123, 10, 1): value will lose the scale when convert to the target data type
         let expr_eq =
-            cast(col("c1"), DataType::Decimal128(10, 1)).eq(lit_decimal(123, 10, 1));
+            cast(col("c1"), LogicalType::Decimal128(10, 1)).eq(lit_decimal(123, 10, 1));
         assert_eq!(optimize_test(expr_eq.clone(), &schema), expr_eq);
 
         // c1 = DECIMAL(1230, 10, 2): value will lose the scale when convert to the target data type
         let expr_eq =
-            cast(col("c1"), DataType::Decimal128(10, 2)).eq(lit_decimal(1230, 10, 2));
+            cast(col("c1"), LogicalType::Decimal128(10, 2)).eq(lit_decimal(1230, 10, 2));
         assert_eq!(optimize_test(expr_eq.clone(), &schema), expr_eq);
     }
 
@@ -674,32 +603,32 @@ mod tests {
         let schema = expr_test_schema();
         // integer to decimal
         // c3 < INT64(16) -> c3 < (CAST(INT64(16) AS DECIMAL(18,2));
-        let expr_lt = try_cast(col("c3"), DataType::Int64).lt(lit(16i64));
+        let expr_lt = try_cast(col("c3"), LogicalType::Int64).lt(lit(16i64));
         let expected = col("c3").lt(lit_decimal(1600, 18, 2));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // c3 < INT64(NULL)
-        let c1_lt_lit_null = cast(col("c3"), DataType::Int64).lt(null_i64());
+        let c1_lt_lit_null = cast(col("c3"), LogicalType::Int64).lt(null_i64());
         let expected = col("c3").lt(null_decimal(18, 2));
         assert_eq!(optimize_test(c1_lt_lit_null, &schema), expected);
 
         // decimal to decimal
         // c3 < Decimal(123,10,0) -> c3 < CAST(DECIMAL(123,10,0) AS DECIMAL(18,2)) -> c3 < DECIMAL(12300,18,2)
         let expr_lt =
-            cast(col("c3"), DataType::Decimal128(10, 0)).lt(lit_decimal(123, 10, 0));
+            cast(col("c3"), LogicalType::Decimal128(10, 0)).lt(lit_decimal(123, 10, 0));
         let expected = col("c3").lt(lit_decimal(12300, 18, 2));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // c3 < Decimal(1230,10,3) -> c3 < CAST(DECIMAL(1230,10,3) AS DECIMAL(18,2)) -> c3 < DECIMAL(123,18,2)
         let expr_lt =
-            cast(col("c3"), DataType::Decimal128(10, 3)).lt(lit_decimal(1230, 10, 3));
+            cast(col("c3"), LogicalType::Decimal128(10, 3)).lt(lit_decimal(1230, 10, 3));
         let expected = col("c3").lt(lit_decimal(123, 18, 2));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // decimal to integer
         // c1 < Decimal(12300, 10, 2) -> c1 < CAST(DECIMAL(12300,10,2) AS INT32) -> c1 < INT32(123)
         let expr_lt =
-            cast(col("c1"), DataType::Decimal128(10, 2)).lt(lit_decimal(12300, 10, 2));
+            cast(col("c1"), LogicalType::Decimal128(10, 2)).lt(lit_decimal(12300, 10, 2));
         let expected = col("c1").lt(lit(123i32));
         assert_eq!(optimize_test(expr_lt, &schema), expected);
     }
@@ -710,21 +639,21 @@ mod tests {
         // internal left type is not supported
         // FLOAT32(C5) in ...
         let expr_lt =
-            cast(col("c5"), DataType::Int64).in_list(vec![lit(12i64), lit(12i64)], false);
+            cast(col("c5"), LogicalType::Int64).in_list(vec![lit(12i64), lit(12i64)], false);
         assert_eq!(optimize_test(expr_lt.clone(), &schema), expr_lt);
 
         // cast(INT32(C1), Float32) in (FLOAT32(1.23), Float32(12), Float32(12))
-        let expr_lt = cast(col("c1"), DataType::Float32)
+        let expr_lt = cast(col("c1"), LogicalType::Float32)
             .in_list(vec![lit(12.0f32), lit(12.0f32), lit(1.23f32)], false);
         assert_eq!(optimize_test(expr_lt.clone(), &schema), expr_lt);
 
         // INT32(C1) in (INT64(99999999999), INT64(12))
-        let expr_lt = cast(col("c1"), DataType::Int64)
+        let expr_lt = cast(col("c1"), LogicalType::Int64)
             .in_list(vec![lit(12i32), lit(99999999999i64)], false);
         assert_eq!(optimize_test(expr_lt.clone(), &schema), expr_lt);
 
         // DECIMAL(C3) in (INT64(12), INT32(12), DECIMAL(128,12,3))
-        let expr_lt = cast(col("c3"), DataType::Decimal128(12, 3)).in_list(
+        let expr_lt = cast(col("c3"), LogicalType::Decimal128(12, 3)).in_list(
             vec![
                 lit_decimal(12, 12, 3),
                 lit_decimal(12, 12, 3),
@@ -740,19 +669,19 @@ mod tests {
         let schema = expr_test_schema();
         // INT32(C1) IN (INT32(12),INT64(24)) -> INT32(C1) IN (INT32(12),INT32(24))
         let expr_lt =
-            cast(col("c1"), DataType::Int64).in_list(vec![lit(12i64), lit(24i64)], false);
+            cast(col("c1"), LogicalType::Int64).in_list(vec![lit(12i64), lit(24i64)], false);
         let expected = col("c1").in_list(vec![lit(12i32), lit(24i32)], false);
         assert_eq!(optimize_test(expr_lt, &schema), expected);
         // INT32(C2) IN (INT64(NULL),INT64(24)) -> INT32(C1) IN (INT32(12),INT32(24))
         let expr_lt =
-            cast(col("c2"), DataType::Int32).in_list(vec![null_i32(), lit(14i32)], false);
+            cast(col("c2"), LogicalType::Int32).in_list(vec![null_i32(), lit(14i32)], false);
         let expected = col("c2").in_list(vec![null_i64(), lit(14i64)], false);
 
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // decimal test case
         // c3 is decimal(18,2)
-        let expr_lt = cast(col("c3"), DataType::Decimal128(19, 3)).in_list(
+        let expr_lt = cast(col("c3"), LogicalType::Decimal128(19, 3)).in_list(
             vec![
                 lit_decimal(12000, 19, 3),
                 lit_decimal(24000, 19, 3),
@@ -773,7 +702,7 @@ mod tests {
         assert_eq!(optimize_test(expr_lt, &schema), expected);
 
         // cast(INT32(12), INT64) IN (.....)
-        let expr_lt = cast(lit(12i32), DataType::Int64)
+        let expr_lt = cast(lit(12i32), LogicalType::Int64)
             .in_list(vec![lit(13i64), lit(12i64)], false);
         let expected = lit(12i32).in_list(vec![lit(13i32), lit(12i32)], false);
         assert_eq!(optimize_test(expr_lt, &schema), expected);
@@ -784,7 +713,7 @@ mod tests {
         let schema = expr_test_schema();
         // c1 < INT64(16) -> c1 < cast(INT32(16))
         // the 16 is within the range of MAX(int32) and MIN(int32), we can cast the 16 to int32(16)
-        let expr_lt = cast(col("c1"), DataType::Int64).lt(lit(16i64)).alias("x");
+        let expr_lt = cast(col("c1"), LogicalType::Int64).lt(lit(16i64)).alias("x");
         let expected = col("c1").lt(lit(16i32)).alias("x");
         assert_eq!(optimize_test(expr_lt, &schema), expected);
     }
@@ -794,9 +723,9 @@ mod tests {
         let schema = expr_test_schema();
         // c1 < INT64(16) OR c1 > INT64(32) -> c1 < INT32(16) OR c1 > INT32(32)
         // the 16 and 32 are within the range of MAX(int32) and MIN(int32), we can cast them to int32
-        let expr_lt = cast(col("c1"), DataType::Int64).lt(lit(16i64)).or(cast(
+        let expr_lt = cast(col("c1"), LogicalType::Int64).lt(lit(16i64)).or(cast(
             col("c1"),
-            DataType::Int64,
+            LogicalType::Int64,
         )
         .gt(lit(32i64)));
         let expected = col("c1").lt(lit(16i32)).or(col("c1").gt(lit(32i32)));
@@ -809,12 +738,12 @@ mod tests {
         // but the type of c6 is uint32
         // the rewriter will not throw error and just return the original expr
         let schema = expr_test_schema();
-        let expr_input = cast(col("c6"), DataType::Float64).eq(lit(0f64));
+        let expr_input = cast(col("c6"), LogicalType::Float64).eq(lit(0f64));
         assert_eq!(optimize_test(expr_input.clone(), &schema), expr_input);
 
         // inlist for unsupported data type
         let expr_input =
-            in_list(cast(col("c6"), DataType::Float64), vec![lit(0f64)], false);
+            in_list(cast(col("c6"), LogicalType::Float64), vec![lit(0f64)], false);
         assert_eq!(optimize_test(expr_input.clone(), &schema), expr_input);
     }
 
@@ -841,17 +770,16 @@ mod tests {
         Arc::new(
             DFSchema::from_unqualifed_fields(
                 vec![
-                    Field::new("c1", DataType::Int32, false),
-                    Field::new("c2", DataType::Int64, false),
-                    Field::new("c3", DataType::Decimal128(18, 2), false),
-                    Field::new("c4", DataType::Decimal128(38, 37), false),
-                    Field::new("c5", DataType::Float32, false),
-                    Field::new("c6", DataType::UInt32, false),
-                    Field::new("ts_nano_none", timestamp_nano_none_type(), false),
-                    Field::new("ts_nano_utf", timestamp_nano_utc_type(), false),
-                    Field::new("str1", DataType::Utf8, false),
-                    Field::new("largestr", DataType::LargeUtf8, false),
-                    Field::new("tag", dictionary_tag_type(), false),
+                    LogicalField::new("c1", LogicalType::Int32, false),
+                    LogicalField::new("c2", LogicalType::Int64, false),
+                    LogicalField::new("c3", LogicalType::Decimal128(18, 2), false),
+                    LogicalField::new("c4", LogicalType::Decimal128(38, 37), false),
+                    LogicalField::new("c5", LogicalType::Float32, false),
+                    LogicalField::new("c6", LogicalType::UInt32, false),
+                    LogicalField::new("ts_nano_none", timestamp_nano_none_type(), false),
+                    LogicalField::new("ts_nano_utf", timestamp_nano_utc_type(), false),
+                    LogicalField::new("str1", LogicalType::Utf8, false),
+                    LogicalField::new("largestr", LogicalType::LargeUtf8, false),
                 ]
                 .into(),
                 HashMap::new(),
@@ -889,19 +817,14 @@ mod tests {
         lit(ScalarValue::Decimal128(None, precision, scale))
     }
 
-    fn timestamp_nano_none_type() -> DataType {
-        DataType::Timestamp(TimeUnit::Nanosecond, None)
+    fn timestamp_nano_none_type() -> LogicalType {
+        LogicalType::Timestamp(TimeUnit::Nanosecond, None)
     }
 
     // this is the type that now() returns
-    fn timestamp_nano_utc_type() -> DataType {
+    fn timestamp_nano_utc_type() -> LogicalType {
         let utc = Some("+0:00".into());
-        DataType::Timestamp(TimeUnit::Nanosecond, utc)
-    }
-
-    // a dictonary type for storing string tags
-    fn dictionary_tag_type() -> DataType {
-        DataType::Dictionary(Box::new(DataType::Int32), Box::new(DataType::Utf8))
+        LogicalType::Timestamp(TimeUnit::Nanosecond, utc)
     }
 
     #[test]
@@ -926,7 +849,7 @@ mod tests {
             for s2 in &scalars {
                 let expected_value = ExpectedCast::Value(s2.clone());
 
-                expect_cast(s1.clone(), s2.data_type(), expected_value);
+                expect_cast(s1.clone(), s2.data_type().into(), expected_value);
             }
         }
     }
@@ -951,28 +874,28 @@ mod tests {
             for s2 in &scalars {
                 let expected_value = ExpectedCast::Value(s2.clone());
 
-                expect_cast(s1.clone(), s2.data_type(), expected_value);
+                expect_cast(s1.clone(), s2.data_type().into(), expected_value);
             }
         }
 
         let max_i32 = ScalarValue::Int32(Some(i32::MAX));
         expect_cast(
             max_i32,
-            DataType::UInt64,
+            LogicalType::UInt64,
             ExpectedCast::Value(ScalarValue::UInt64(Some(i32::MAX as u64))),
         );
 
         let min_i32 = ScalarValue::Int32(Some(i32::MIN));
         expect_cast(
             min_i32,
-            DataType::Int64,
+            LogicalType::Int64,
             ExpectedCast::Value(ScalarValue::Int64(Some(i32::MIN as i64))),
         );
 
         let max_i64 = ScalarValue::Int64(Some(i64::MAX));
         expect_cast(
             max_i64,
-            DataType::UInt64,
+            LogicalType::UInt64,
             ExpectedCast::Value(ScalarValue::UInt64(Some(i64::MAX as u64))),
         );
     }
@@ -984,28 +907,28 @@ mod tests {
         let max_i64 = ScalarValue::Int64(Some(i64::MAX));
         let max_u64 = ScalarValue::UInt64(Some(u64::MAX));
 
-        expect_cast(max_i64.clone(), DataType::Int8, ExpectedCast::NoValue);
+        expect_cast(max_i64.clone(), LogicalType::Int8, ExpectedCast::NoValue);
 
-        expect_cast(max_i64.clone(), DataType::Int16, ExpectedCast::NoValue);
+        expect_cast(max_i64.clone(), LogicalType::Int16, ExpectedCast::NoValue);
 
-        expect_cast(max_i64, DataType::Int32, ExpectedCast::NoValue);
+        expect_cast(max_i64, LogicalType::Int32, ExpectedCast::NoValue);
 
-        expect_cast(max_u64, DataType::Int64, ExpectedCast::NoValue);
+        expect_cast(max_u64, LogicalType::Int64, ExpectedCast::NoValue);
 
-        expect_cast(min_i64, DataType::UInt64, ExpectedCast::NoValue);
+        expect_cast(min_i64, LogicalType::UInt64, ExpectedCast::NoValue);
 
-        expect_cast(min_i32, DataType::UInt64, ExpectedCast::NoValue);
+        expect_cast(min_i32, LogicalType::UInt64, ExpectedCast::NoValue);
 
         // decimal out of range
         expect_cast(
             ScalarValue::Decimal128(Some(99999999999999999999999999999999999900), 38, 0),
-            DataType::Int64,
+            LogicalType::Int64,
             ExpectedCast::NoValue,
         );
 
         expect_cast(
             ScalarValue::Decimal128(Some(-9999999999999999999999999999999999), 37, 1),
-            DataType::Int64,
+            LogicalType::Int64,
             ExpectedCast::NoValue,
         );
     }
@@ -1014,19 +937,19 @@ mod tests {
     fn test_try_decimal_cast_in_range() {
         expect_cast(
             ScalarValue::Decimal128(Some(12300), 5, 2),
-            DataType::Decimal128(3, 0),
+            LogicalType::Decimal128(3, 0),
             ExpectedCast::Value(ScalarValue::Decimal128(Some(123), 3, 0)),
         );
 
         expect_cast(
             ScalarValue::Decimal128(Some(12300), 5, 2),
-            DataType::Decimal128(8, 0),
+            LogicalType::Decimal128(8, 0),
             ExpectedCast::Value(ScalarValue::Decimal128(Some(123), 8, 0)),
         );
 
         expect_cast(
             ScalarValue::Decimal128(Some(12300), 5, 2),
-            DataType::Decimal128(8, 5),
+            LogicalType::Decimal128(8, 5),
             ExpectedCast::Value(ScalarValue::Decimal128(Some(12300000), 8, 5)),
         );
     }
@@ -1036,14 +959,14 @@ mod tests {
         // decimal would lose precision
         expect_cast(
             ScalarValue::Decimal128(Some(12345), 5, 2),
-            DataType::Decimal128(3, 0),
+            LogicalType::Decimal128(3, 0),
             ExpectedCast::NoValue,
         );
 
         // decimal would lose precision
         expect_cast(
             ScalarValue::Decimal128(Some(12300), 5, 2),
-            DataType::Decimal128(2, 0),
+            LogicalType::Decimal128(2, 0),
             ExpectedCast::NoValue,
         );
     }
@@ -1084,11 +1007,11 @@ mod tests {
             // so double check it here
             assert_eq!(lit_tz_none, lit_tz_utc);
 
-            // e.g. DataType::Timestamp(_, None)
-            let dt_tz_none = lit_tz_none.data_type();
+            // e.g. LogicalType::Timestamp(_, None)
+            let dt_tz_none: LogicalType = lit_tz_none.data_type().into();
 
-            // e.g. DataType::Timestamp(_, Some(utc))
-            let dt_tz_utc = lit_tz_utc.data_type();
+            // e.g. LogicalType::Timestamp(_, Some(utc))
+            let dt_tz_utc: LogicalType = lit_tz_utc.data_type().into();
 
             // None <--> None
             expect_cast(
@@ -1121,7 +1044,7 @@ mod tests {
             // timestamp to int64
             expect_cast(
                 lit_tz_utc.clone(),
-                DataType::Int64,
+                LogicalType::Int64,
                 ExpectedCast::Value(ScalarValue::Int64(Some(12345))),
             );
 
@@ -1142,7 +1065,7 @@ mod tests {
             // timestamp to string (not supported yet)
             expect_cast(
                 lit_tz_utc.clone(),
-                DataType::LargeUtf8,
+                LogicalType::LargeUtf8,
                 ExpectedCast::NoValue,
             );
         }
@@ -1153,7 +1076,7 @@ mod tests {
         // int64 to list
         expect_cast(
             ScalarValue::Int64(Some(12345)),
-            DataType::List(Arc::new(Field::new("f", DataType::Int32, true))),
+            LogicalType::new_list(LogicalType::Int32, true),
             ExpectedCast::NoValue,
         );
     }
@@ -1171,7 +1094,7 @@ mod tests {
     /// casting is consistent with the Arrow kernels
     fn expect_cast(
         literal: ScalarValue,
-        target_type: DataType,
+        target_type: LogicalType,
         expected_result: ExpectedCast,
     ) {
         let actual_value = try_cast_literal_to_type(&literal, &target_type);
@@ -1199,7 +1122,7 @@ mod tests {
                     .expect("Failed to convert to array of size");
                 let cast_array = cast_with_options(
                     &literal_array,
-                    &target_type,
+                    &target_type.physical_type(),
                     &CastOptions::default(),
                 )
                 .expect("Expected to be cast array with arrow cast kernel");
@@ -1212,9 +1135,9 @@ mod tests {
                 // Verify that for timestamp types the timezones are the same
                 // (ScalarValue::cmp doesn't account for timezones);
                 if let (
-                    DataType::Timestamp(left_unit, left_tz),
-                    DataType::Timestamp(right_unit, right_tz),
-                ) = (actual_value.data_type(), expected_value.data_type())
+                    LogicalType::Timestamp(left_unit, left_tz),
+                    LogicalType::Timestamp(right_unit, right_tz),
+                ) = (actual_value.data_type().into(), expected_value.data_type().into())
                 {
                     assert_eq!(left_unit, right_unit);
                     assert_eq!(left_tz, right_tz);
@@ -1234,7 +1157,7 @@ mod tests {
         // same timestamp
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampNanosecond(Some(123456), None),
-            &DataType::Timestamp(TimeUnit::Nanosecond, None),
+            &LogicalType::Timestamp(TimeUnit::Nanosecond, None),
         )
         .unwrap();
 
@@ -1246,7 +1169,7 @@ mod tests {
         // TimestampNanosecond to TimestampMicrosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampNanosecond(Some(123456), None),
-            &DataType::Timestamp(TimeUnit::Microsecond, None),
+            &LogicalType::Timestamp(TimeUnit::Microsecond, None),
         )
         .unwrap();
 
@@ -1258,7 +1181,7 @@ mod tests {
         // TimestampNanosecond to TimestampMillisecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampNanosecond(Some(123456), None),
-            &DataType::Timestamp(TimeUnit::Millisecond, None),
+            &LogicalType::Timestamp(TimeUnit::Millisecond, None),
         )
         .unwrap();
 
@@ -1267,7 +1190,7 @@ mod tests {
         // TimestampNanosecond to TimestampSecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampNanosecond(Some(123456), None),
-            &DataType::Timestamp(TimeUnit::Second, None),
+            &LogicalType::Timestamp(TimeUnit::Second, None),
         )
         .unwrap();
 
@@ -1276,7 +1199,7 @@ mod tests {
         // TimestampMicrosecond to TimestampNanosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMicrosecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Nanosecond, None),
+            &LogicalType::Timestamp(TimeUnit::Nanosecond, None),
         )
         .unwrap();
 
@@ -1288,7 +1211,7 @@ mod tests {
         // TimestampMicrosecond to TimestampMillisecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMicrosecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Millisecond, None),
+            &LogicalType::Timestamp(TimeUnit::Millisecond, None),
         )
         .unwrap();
 
@@ -1297,7 +1220,7 @@ mod tests {
         // TimestampMicrosecond to TimestampSecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMicrosecond(Some(123456789), None),
-            &DataType::Timestamp(TimeUnit::Second, None),
+            &LogicalType::Timestamp(TimeUnit::Second, None),
         )
         .unwrap();
         assert_eq!(new_scalar, ScalarValue::TimestampSecond(Some(123), None));
@@ -1305,7 +1228,7 @@ mod tests {
         // TimestampMillisecond to TimestampNanosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMillisecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Nanosecond, None),
+            &LogicalType::Timestamp(TimeUnit::Nanosecond, None),
         )
         .unwrap();
         assert_eq!(
@@ -1316,7 +1239,7 @@ mod tests {
         // TimestampMillisecond to TimestampMicrosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMillisecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Microsecond, None),
+            &LogicalType::Timestamp(TimeUnit::Microsecond, None),
         )
         .unwrap();
         assert_eq!(
@@ -1326,7 +1249,7 @@ mod tests {
         // TimestampMillisecond to TimestampSecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampMillisecond(Some(123456789), None),
-            &DataType::Timestamp(TimeUnit::Second, None),
+            &LogicalType::Timestamp(TimeUnit::Second, None),
         )
         .unwrap();
         assert_eq!(new_scalar, ScalarValue::TimestampSecond(Some(123456), None));
@@ -1334,7 +1257,7 @@ mod tests {
         // TimestampSecond to TimestampNanosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampSecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Nanosecond, None),
+            &LogicalType::Timestamp(TimeUnit::Nanosecond, None),
         )
         .unwrap();
         assert_eq!(
@@ -1345,7 +1268,7 @@ mod tests {
         // TimestampSecond to TimestampMicrosecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampSecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Microsecond, None),
+            &LogicalType::Timestamp(TimeUnit::Microsecond, None),
         )
         .unwrap();
         assert_eq!(
@@ -1356,7 +1279,7 @@ mod tests {
         // TimestampSecond to TimestampMillisecond
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampSecond(Some(123), None),
-            &DataType::Timestamp(TimeUnit::Millisecond, None),
+            &LogicalType::Timestamp(TimeUnit::Millisecond, None),
         )
         .unwrap();
         assert_eq!(
@@ -1367,7 +1290,7 @@ mod tests {
         // overflow
         let new_scalar = try_cast_literal_to_type(
             &ScalarValue::TimestampSecond(Some(i64::MAX), None),
-            &DataType::Timestamp(TimeUnit::Millisecond, None),
+            &LogicalType::Timestamp(TimeUnit::Millisecond, None),
         )
         .unwrap();
         assert_eq!(new_scalar, ScalarValue::TimestampMillisecond(None, None));
@@ -1384,33 +1307,8 @@ mod tests {
             for s2 in &scalars {
                 let expected_value = ExpectedCast::Value(s2.clone());
 
-                expect_cast(s1.clone(), s2.data_type(), expected_value);
+                expect_cast(s1.clone(), s2.data_type().into(), expected_value);
             }
         }
     }
-    #[test]
-    fn test_try_cast_to_dictionary_type() {
-        fn dictionary_type(t: DataType) -> DataType {
-            DataType::Dictionary(Box::new(DataType::Int32), Box::new(t))
-        }
-        fn dictionary_value(value: ScalarValue) -> ScalarValue {
-            ScalarValue::Dictionary(Box::new(DataType::Int32), Box::new(value))
-        }
-        let scalars = vec![
-            ScalarValue::from("string"),
-            ScalarValue::LargeUtf8(Some("string".to_owned())),
-        ];
-        for s in &scalars {
-            expect_cast(
-                s.clone(),
-                dictionary_type(s.data_type()),
-                ExpectedCast::Value(dictionary_value(s.clone())),
-            );
-            expect_cast(
-                dictionary_value(s.clone()),
-                s.data_type(),
-                ExpectedCast::Value(s.clone()),
-            )
-        }
-    }
 }
diff --git a/datafusion/optimizer/tests/optimizer_integration.rs b/datafusion/optimizer/tests/optimizer_integration.rs
index c501d5aaa4bf..33678a98da08 100644
--- a/datafusion/optimizer/tests/optimizer_integration.rs
+++ b/datafusion/optimizer/tests/optimizer_integration.rs
@@ -23,6 +23,7 @@ use arrow::datatypes::{DataType, Field, Schema, SchemaRef, TimeUnit};
 
 use datafusion_common::config::ConfigOptions;
 use datafusion_common::{plan_err, Result};
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::test::function_stub::sum_udaf;
 use datafusion_expr::{AggregateUDF, LogicalPlan, ScalarUDF, TableSource, WindowUDF};
 use datafusion_functions_aggregate::average::avg_udaf;
@@ -399,7 +400,7 @@ impl ContextProvider for MyContextProvider {
         self.udafs.get(name).cloned()
     }
 
-    fn get_variable_type(&self, _variable_names: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, _variable_names: &[String]) -> Option<LogicalType> {
         None
     }
 
diff --git a/datafusion/physical-expr-common/src/utils.rs b/datafusion/physical-expr-common/src/utils.rs
index d5cd3c6f4af0..39305401288d 100644
--- a/datafusion/physical-expr-common/src/utils.rs
+++ b/datafusion/physical-expr-common/src/utils.rs
@@ -22,6 +22,7 @@ use arrow::compute::{and_kleene, is_not_null, SlicesIterator};
 use arrow::datatypes::Schema;
 
 use datafusion_common::{exec_err, Result};
+use datafusion_common::logical_type::extension::ExtensionType;
 use datafusion_expr::expr::Alias;
 use datafusion_expr::sort_properties::ExprProperties;
 use datafusion_expr::Expr;
@@ -127,7 +128,7 @@ pub fn limited_convert_logical_expr_to_physical_expr(
                 cast_expr.expr.as_ref(),
                 schema,
             )?,
-            cast_expr.data_type.clone(),
+            cast_expr.data_type.physical_type(),
             None,
         ))),
         Expr::Literal(value) => Ok(Arc::new(Literal::new(value.clone()))),
diff --git a/datafusion/physical-expr/src/expressions/in_list.rs b/datafusion/physical-expr/src/expressions/in_list.rs
index 53c790ff6b54..98d501c97854 100644
--- a/datafusion/physical-expr/src/expressions/in_list.rs
+++ b/datafusion/physical-expr/src/expressions/in_list.rs
@@ -429,7 +429,7 @@ pub fn in_list(
     let expr_data_type = expr.data_type(schema)?;
     for list_expr in list.iter() {
         let list_expr_data_type = list_expr.data_type(schema)?;
-        if !DFSchema::datatype_is_logically_equal(&expr_data_type, &list_expr_data_type) {
+        if !DFSchema::datatype_is_logically_equal(&expr_data_type.clone().into(), &list_expr_data_type.clone().into()) {
             return internal_err!(
                 "The data type inlist should be same, the value type is {expr_data_type}, one of list expr type is {list_expr_data_type}"
             );
diff --git a/datafusion/physical-expr/src/expressions/negative.rs b/datafusion/physical-expr/src/expressions/negative.rs
index aed2675e0447..f3ed3526b45a 100644
--- a/datafusion/physical-expr/src/expressions/negative.rs
+++ b/datafusion/physical-expr/src/expressions/negative.rs
@@ -160,7 +160,7 @@ pub fn negative(
     arg: Arc<dyn PhysicalExpr>,
     input_schema: &Schema,
 ) -> Result<Arc<dyn PhysicalExpr>> {
-    let data_type = arg.data_type(input_schema)?;
+    let data_type = arg.data_type(input_schema)?.into();
     if is_null(&data_type) {
         Ok(arg)
     } else if !is_signed_numeric(&data_type)
diff --git a/datafusion/physical-expr/src/planner.rs b/datafusion/physical-expr/src/planner.rs
index 8fe99cdca591..ae0f6e455532 100644
--- a/datafusion/physical-expr/src/planner.rs
+++ b/datafusion/physical-expr/src/planner.rs
@@ -24,9 +24,9 @@ use crate::{
 };
 
 use arrow::datatypes::Schema;
-use datafusion_common::{
-    exec_err, not_impl_err, plan_err, DFSchema, Result, ScalarValue, ToDFSchema,
-};
+use datafusion_common::{exec_err, not_impl_err, plan_err, DFSchema, Result, ScalarValue, ToDFSchema};
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 use datafusion_expr::execution_props::ExecutionProps;
 use datafusion_expr::expr::{Alias, Cast, InList, ScalarFunction};
 use datafusion_expr::var_provider::is_system_variables;
@@ -259,12 +259,12 @@ pub fn create_physical_expr(
         Expr::Cast(Cast { expr, data_type }) => expressions::cast(
             create_physical_expr(expr, input_dfschema, execution_props)?,
             input_schema,
-            data_type.clone(),
+            data_type.clone().physical_type(),
         ),
         Expr::TryCast(TryCast { expr, data_type }) => expressions::try_cast(
             create_physical_expr(expr, input_dfschema, execution_props)?,
             input_schema,
-            data_type.clone(),
+            data_type.clone().physical_type(),
         ),
         Expr::Not(expr) => {
             expressions::not(create_physical_expr(expr, input_dfschema, execution_props)?)
@@ -359,7 +359,7 @@ where
 
 /// Convert a logical expression to a physical expression (without any simplification, etc)
 pub fn logical2physical(expr: &Expr, schema: &Schema) -> Arc<dyn PhysicalExpr> {
-    let df_schema = schema.clone().to_dfschema().unwrap();
+    let df_schema = LogicalSchema::from(schema.clone()).to_dfschema().unwrap();
     let execution_props = ExecutionProps::new();
     create_physical_expr(expr, &df_schema, &execution_props).unwrap()
 }
@@ -378,7 +378,7 @@ mod tests {
         let expr = col("letter").eq(lit("A"));
 
         let schema = Schema::new(vec![Field::new("letter", DataType::Utf8, false)]);
-        let df_schema = DFSchema::try_from_qualified_schema("data", &schema)?;
+        let df_schema = DFSchema::try_from_qualified_schema("data", &schema.clone().into())?;
         let p = create_physical_expr(&expr, &df_schema, &ExecutionProps::new())?;
 
         let batch = RecordBatch::try_new(
diff --git a/datafusion/physical-expr/src/utils/guarantee.rs b/datafusion/physical-expr/src/utils/guarantee.rs
index 070034116fb4..67d20837afdc 100644
--- a/datafusion/physical-expr/src/utils/guarantee.rs
+++ b/datafusion/physical-expr/src/utils/guarantee.rs
@@ -420,11 +420,10 @@ impl<'a> ColOpLit<'a> {
 #[cfg(test)]
 mod test {
     use std::sync::OnceLock;
-
+    use arrow_schema::{DataType, Field, Schema, SchemaRef};
     use super::*;
     use crate::planner::logical2physical;
 
-    use arrow_schema::{DataType, Field, Schema, SchemaRef};
     use datafusion_expr::expr_fn::*;
     use datafusion_expr::{lit, Expr};
 
@@ -835,7 +834,7 @@ mod test {
     fn test_analyze(expr: Expr, expected: Vec<LiteralGuarantee>) {
         println!("Begin analyze of {expr}");
         let schema = schema();
-        let physical_expr = logical2physical(&expr, &schema);
+        let physical_expr = logical2physical(&expr, &schema.as_ref().clone().into());
 
         let actual = LiteralGuarantee::analyze(&physical_expr);
         assert_eq!(
diff --git a/datafusion/proto-common/src/from_proto/mod.rs b/datafusion/proto-common/src/from_proto/mod.rs
index de9fede9ee86..6f54ac19626f 100644
--- a/datafusion/proto-common/src/from_proto/mod.rs
+++ b/datafusion/proto-common/src/from_proto/mod.rs
@@ -42,6 +42,8 @@ use datafusion_common::{
     Column, ColumnStatistics, Constraint, Constraints, DFSchema, DFSchemaRef,
     DataFusionError, JoinSide, ScalarValue, Statistics, TableReference,
 };
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
 
 #[derive(Debug)]
 pub enum Error {
@@ -158,10 +160,10 @@ impl TryFrom<&protobuf::DfSchema> for DFSchema {
         df_schema: &protobuf::DfSchema,
     ) -> datafusion_common::Result<Self, Self::Error> {
         let df_fields = df_schema.columns.clone();
-        let qualifiers_and_fields: Vec<(Option<TableReference>, Arc<Field>)> = df_fields
+        let qualifiers_and_fields: Vec<(Option<TableReference>, Arc<LogicalField>)> = df_fields
             .iter()
             .map(|df_field| {
-                let field: Field = df_field.field.as_ref().required("field")?;
+                let field: LogicalField = df_field.field.as_ref().required("field")?;
                 Ok((
                     df_field
                         .qualifier
@@ -190,6 +192,16 @@ impl TryFrom<protobuf::DfSchema> for DFSchemaRef {
     }
 }
 
+impl TryFrom<&protobuf::ArrowType> for LogicalType {
+    type Error = Error;
+
+    fn try_from(
+        arrow_type: &protobuf::ArrowType,
+    ) -> datafusion_common::Result<Self, Self::Error> {
+        DataType::try_from(arrow_type).map(|t| t.into())
+    }
+}
+
 impl TryFrom<&protobuf::ArrowType> for DataType {
     type Error = Error;
 
@@ -332,6 +344,14 @@ impl TryFrom<&protobuf::Field> for Field {
     }
 }
 
+
+impl TryFrom<&protobuf::Field> for LogicalField {
+    type Error = Error;
+    fn try_from(field: &protobuf::Field) -> Result<Self, Self::Error> {
+        Field::try_from(field).map(|t| t.into())
+    }
+}
+
 impl TryFrom<&protobuf::Schema> for Schema {
     type Error = Error;
 
diff --git a/datafusion/proto-common/src/to_proto/mod.rs b/datafusion/proto-common/src/to_proto/mod.rs
index 877043f66809..d343554e6fe6 100644
--- a/datafusion/proto-common/src/to_proto/mod.rs
+++ b/datafusion/proto-common/src/to_proto/mod.rs
@@ -23,10 +23,7 @@ use crate::protobuf_common::{
 };
 use arrow::array::{ArrayRef, RecordBatch};
 use arrow::csv::WriterBuilder;
-use arrow::datatypes::{
-    DataType, Field, IntervalDayTimeType, IntervalMonthDayNanoType, IntervalUnit, Schema,
-    SchemaRef, TimeUnit, UnionMode,
-};
+use arrow::datatypes::{DataType, Field, IntervalDayTimeType, IntervalMonthDayNanoType, IntervalUnit, Schema, SchemaRef, TimeUnit, UnionMode};
 use arrow::ipc::writer::{DictionaryTracker, IpcDataGenerator};
 use datafusion_common::{
     config::{
@@ -39,6 +36,8 @@ use datafusion_common::{
     Column, ColumnStatistics, Constraint, Constraints, DFSchema, DFSchemaRef,
     DataFusionError, JoinSide, ScalarValue, Statistics,
 };
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 
 #[derive(Debug)]
 pub enum Error {
@@ -112,6 +111,17 @@ impl TryFrom<&DataType> for protobuf::ArrowType {
     }
 }
 
+impl TryFrom<&LogicalType> for protobuf::ArrowType {
+    type Error = Error;
+
+    fn try_from(val: &LogicalType) -> Result<Self, Self::Error> {
+        let arrow_type_enum: ArrowTypeEnum = (&val.physical_type()).try_into()?;
+        Ok(Self {
+            arrow_type_enum: Some(arrow_type_enum),
+        })
+    }
+}
+
 impl TryFrom<&DataType> for protobuf::arrow_type::ArrowTypeEnum {
     type Error = Error;
 
@@ -262,8 +272,9 @@ impl TryFrom<&DFSchema> for protobuf::DfSchema {
         let columns = s
             .iter()
             .map(|(qualifier, field)| {
+                let field: Field = field.as_ref().clone().into();
                 Ok(protobuf::DfField {
-                    field: Some(field.as_ref().try_into()?),
+                    field: Some((&field).try_into()?),
                     qualifier: qualifier.map(|r| protobuf::ColumnRelation {
                         relation: r.to_string(),
                     }),
diff --git a/datafusion/proto/src/logical_plan/mod.rs b/datafusion/proto/src/logical_plan/mod.rs
index cdb9d5260a0f..06e15d19b8f8 100644
--- a/datafusion/proto/src/logical_plan/mod.rs
+++ b/datafusion/proto/src/logical_plan/mod.rs
@@ -65,7 +65,9 @@ use datafusion_expr::{
 
 use prost::bytes::BufMut;
 use prost::Message;
-
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_proto_common::ArrowType;
 use self::to_proto::serialize_expr;
 
 pub mod file_formats;
@@ -830,10 +832,10 @@ impl AsLogicalPlan for LogicalPlanNode {
             LogicalPlanType::Prepare(prepare) => {
                 let input: LogicalPlan =
                     into_logical_plan!(prepare.input, ctx, extension_codec)?;
-                let data_types: Vec<DataType> = prepare
+                let data_types: Vec<LogicalType> = prepare
                     .data_types
                     .iter()
-                    .map(DataType::try_from)
+                    .map(|t| DataType::try_from(t).map(|t| t.into()))
                     .collect::<Result<_, _>>()?;
                 LogicalPlanBuilder::from(input)
                     .prepare(prepare.name.clone(), data_types)?
@@ -1554,8 +1556,8 @@ impl AsLogicalPlan for LogicalPlanNode {
                             name: name.clone(),
                             data_types: data_types
                                 .iter()
-                                .map(|t| t.try_into())
-                                .collect::<Result<Vec<_>, _>>()?,
+                                .map(|t| (&t.physical_type()).try_into())
+                                .collect::<Result<Vec<ArrowType>, _>>()?,
                             input: Some(Box::new(input)),
                         },
                     ))),
diff --git a/datafusion/proto/tests/cases/roundtrip_logical_plan.rs b/datafusion/proto/tests/cases/roundtrip_logical_plan.rs
index d54078b72bb7..03a996c12dcd 100644
--- a/datafusion/proto/tests/cases/roundtrip_logical_plan.rs
+++ b/datafusion/proto/tests/cases/roundtrip_logical_plan.rs
@@ -26,6 +26,8 @@ use arrow::datatypes::{
     DataType, Field, Fields, Int32Type, IntervalDayTimeType, IntervalMonthDayNanoType,
     IntervalUnit, Schema, SchemaRef, TimeUnit, UnionFields, UnionMode,
 };
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::LogicalType;
 use datafusion::datasource::file_format::arrow::ArrowFormatFactory;
 use datafusion::datasource::file_format::csv::CsvFormatFactory;
 use datafusion::datasource::file_format::format_as_file_type;
@@ -583,7 +585,7 @@ async fn roundtrip_expr_api() -> Result<()> {
 
     // list of expressions to round trip
     let expr_list = vec![
-        encode(col("a").cast_to(&DataType::Utf8, &schema)?, lit("hex")),
+        encode(col("a").cast_to(&LogicalType::Utf8, &schema)?, lit("hex")),
         decode(lit("1234"), lit("hex")),
         array_to_string(make_array(vec![lit(1), lit(2), lit(3)]), lit(",")),
         array_dims(make_array(vec![lit(1), lit(2), lit(3)])),
@@ -691,7 +693,7 @@ async fn roundtrip_expr_api() -> Result<()> {
         bit_and(lit(2)),
         bit_or(lit(2)),
         bit_xor(lit(2)),
-        string_agg(col("a").cast_to(&DataType::Utf8, &schema)?, lit("|")),
+        string_agg(col("a").cast_to(&LogicalType::Utf8, &schema)?, lit("|")),
         bool_and(lit(true)),
         bool_or(lit(true)),
     ];
@@ -1548,11 +1550,11 @@ fn roundtrip_schema() {
 fn roundtrip_dfschema() {
     let dfschema = DFSchema::new_with_metadata(
         vec![
-            (None, Arc::new(Field::new("a", DataType::Int64, false))),
+            (None, Arc::new(LogicalField::new("a", LogicalType::Int64, false))),
             (
                 Some("t".into()),
                 Arc::new(
-                    Field::new("b", DataType::Decimal128(15, 2), true).with_metadata(
+                    LogicalField::new("b", LogicalType::Decimal128(15, 2), true).with_metadata(
                         HashMap::from([(String::from("k1"), String::from("v1"))]),
                     ),
                 ),
@@ -1681,7 +1683,7 @@ fn roundtrip_null_literal() {
 
 #[test]
 fn roundtrip_cast() {
-    let test_expr = Expr::Cast(Cast::new(Box::new(lit(1.0_f32)), DataType::Boolean));
+    let test_expr = Expr::Cast(Cast::new(Box::new(lit(1.0_f32)), LogicalType::Boolean));
 
     let ctx = SessionContext::new();
     roundtrip_expr_test(test_expr, ctx);
@@ -1690,13 +1692,13 @@ fn roundtrip_cast() {
 #[test]
 fn roundtrip_try_cast() {
     let test_expr =
-        Expr::TryCast(TryCast::new(Box::new(lit(1.0_f32)), DataType::Boolean));
+        Expr::TryCast(TryCast::new(Box::new(lit(1.0_f32)), LogicalType::Boolean));
 
     let ctx = SessionContext::new();
     roundtrip_expr_test(test_expr, ctx);
 
     let test_expr =
-        Expr::TryCast(TryCast::new(Box::new(lit("not a bool")), DataType::Boolean));
+        Expr::TryCast(TryCast::new(Box::new(lit("not a bool")), LogicalType::Boolean));
 
     let ctx = SessionContext::new();
     roundtrip_expr_test(test_expr, ctx);
diff --git a/datafusion/sql/examples/sql.rs b/datafusion/sql/examples/sql.rs
index aee4cf5a38ed..159bf46f97c6 100644
--- a/datafusion/sql/examples/sql.rs
+++ b/datafusion/sql/examples/sql.rs
@@ -30,6 +30,7 @@ use datafusion_sql::{
     TableReference,
 };
 use std::{collections::HashMap, sync::Arc};
+use datafusion_common::logical_type::LogicalType;
 
 fn main() {
     let sql = "SELECT \
@@ -132,7 +133,7 @@ impl ContextProvider for MyContextProvider {
         self.udafs.get(name).cloned()
     }
 
-    fn get_variable_type(&self, _variable_names: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, _variable_names: &[String]) -> Option<LogicalType> {
         None
     }
 
diff --git a/datafusion/sql/src/expr/function.rs b/datafusion/sql/src/expr/function.rs
index ea460cb3efc2..a1e4719d7c70 100644
--- a/datafusion/sql/src/expr/function.rs
+++ b/datafusion/sql/src/expr/function.rs
@@ -16,7 +16,6 @@
 // under the License.
 
 use crate::planner::{ContextProvider, PlannerContext, SqlToRel};
-use arrow_schema::DataType;
 use datafusion_common::{
     internal_datafusion_err, not_impl_err, plan_datafusion_err, plan_err, DFSchema,
     Dependency, Result,
@@ -36,6 +35,7 @@ use sqlparser::ast::{
 };
 use std::str::FromStr;
 use strum::IntoEnumIterator;
+use datafusion_common::logical_type::LogicalType;
 
 /// Suggest a valid function based on an invalid input function name
 pub fn suggest_valid_function(
@@ -474,11 +474,11 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     pub(crate) fn check_unnest_arg(arg: &Expr, schema: &DFSchema) -> Result<()> {
         // Check argument type, array types are supported
         match arg.get_type(schema)? {
-            DataType::List(_)
-            | DataType::LargeList(_)
-            | DataType::FixedSizeList(_, _)
-            | DataType::Struct(_) => Ok(()),
-            DataType::Null => {
+            LogicalType::List(_)
+            | LogicalType::LargeList(_)
+            | LogicalType::FixedSizeList(_, _)
+            | LogicalType::Struct(_) => Ok(()),
+            LogicalType::Null => {
                 not_impl_err!("unnest() does not support null yet")
             }
             _ => {
diff --git a/datafusion/sql/src/expr/identifier.rs b/datafusion/sql/src/expr/identifier.rs
index d297b2e4df5b..87419d97351e 100644
--- a/datafusion/sql/src/expr/identifier.rs
+++ b/datafusion/sql/src/expr/identifier.rs
@@ -16,13 +16,13 @@
 // under the License.
 
 use crate::planner::{ContextProvider, PlannerContext, SqlToRel};
-use arrow_schema::Field;
 use datafusion_common::{
     internal_err, plan_datafusion_err, Column, DFSchema, DataFusionError, Result,
     ScalarValue, TableReference,
 };
 use datafusion_expr::{expr::ScalarFunction, lit, Case, Expr};
 use sqlparser::ast::{Expr as SQLExpr, Ident};
+use datafusion_common::logical_type::field::LogicalField;
 
 impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     pub(super) fn sql_identifier_to_expr(
@@ -280,7 +280,7 @@ fn search_dfschema<'ids, 'schema>(
     ids: &'ids [String],
     schema: &'schema DFSchema,
 ) -> Option<(
-    &'schema Field,
+    &'schema LogicalField,
     Option<&'schema TableReference>,
     &'ids [String],
 )> {
diff --git a/datafusion/sql/src/expr/mod.rs b/datafusion/sql/src/expr/mod.rs
index a8af37ee6a37..04ecdce3f164 100644
--- a/datafusion/sql/src/expr/mod.rs
+++ b/datafusion/sql/src/expr/mod.rs
@@ -15,7 +15,6 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use arrow_schema::DataType;
 use arrow_schema::TimeUnit;
 use datafusion_common::utils::list_ndims;
 use sqlparser::ast::{CastKind, Expr as SQLExpr, Subscript, TrimWhereField, Value};
@@ -24,6 +23,8 @@ use datafusion_common::{
     internal_datafusion_err, internal_err, not_impl_err, plan_err, DFSchema, Result,
     ScalarValue,
 };
+use datafusion_common::logical_type::extension::ExtensionType;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::expr::InList;
 use datafusion_expr::expr::ScalarFunction;
 use datafusion_expr::{
@@ -113,8 +114,8 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         if op == Operator::StringConcat {
             let left_type = left.get_type(schema)?;
             let right_type = right.get_type(schema)?;
-            let left_list_ndims = list_ndims(&left_type);
-            let right_list_ndims = list_ndims(&right_type);
+            let left_list_ndims = list_ndims(&left_type.physical_type());
+            let right_list_ndims = list_ndims(&right_type.physical_type());
 
             // We determine the target function to rewrite based on the list n-dimension, the check is not exact but sufficient.
             // The exact validity check is handled in the actual function, so even if there is 3d list appended with 1d list, it is also fine to rewrite.
@@ -351,12 +352,12 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                 // numeric constants are treated as seconds (rather as nanoseconds)
                 // to align with postgres / duckdb semantics
                 let expr = match &dt {
-                    DataType::Timestamp(TimeUnit::Nanosecond, tz)
-                        if expr.get_type(schema)? == DataType::Int64 =>
+                    LogicalType::Timestamp(TimeUnit::Nanosecond, tz)
+                        if expr.get_type(schema)? == LogicalType::Int64 =>
                     {
                         Expr::Cast(Cast::new(
                             Box::new(expr),
-                            DataType::Timestamp(TimeUnit::Second, tz.clone()),
+                            LogicalType::Timestamp(TimeUnit::Second, tz.clone()),
                         ))
                     }
                     _ => expr,
@@ -635,7 +636,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                 )?),
                 match *time_zone {
                     SQLExpr::Value(Value::SingleQuotedString(s)) => {
-                        DataType::Timestamp(TimeUnit::Nanosecond, Some(s.into()))
+                        LogicalType::Timestamp(TimeUnit::Nanosecond, Some(s.into()))
                     }
                     _ => {
                         return not_impl_err!(
@@ -813,7 +814,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     ) -> Result<Expr> {
         let pattern = self.sql_expr_to_logical_expr(pattern, schema, planner_context)?;
         let pattern_type = pattern.get_type(schema)?;
-        if pattern_type != DataType::Utf8 && pattern_type != DataType::Null {
+        if pattern_type != LogicalType::Utf8 && pattern_type != LogicalType::Null {
             return plan_err!("Invalid pattern in LIKE expression");
         }
         let escape_char = if let Some(char) = escape_char {
@@ -844,7 +845,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     ) -> Result<Expr> {
         let pattern = self.sql_expr_to_logical_expr(pattern, schema, planner_context)?;
         let pattern_type = pattern.get_type(schema)?;
-        if pattern_type != DataType::Utf8 && pattern_type != DataType::Null {
+        if pattern_type != LogicalType::Utf8 && pattern_type != LogicalType::Null {
             return plan_err!("Invalid pattern in SIMILAR TO expression");
         }
         let escape_char = if let Some(char) = escape_char {
@@ -1023,6 +1024,7 @@ mod tests {
     use std::sync::Arc;
 
     use arrow::datatypes::{Field, Schema};
+    use arrow_schema::DataType;
     use sqlparser::dialect::GenericDialect;
     use sqlparser::parser::Parser;
 
@@ -1074,7 +1076,7 @@ mod tests {
             None
         }
 
-        fn get_variable_type(&self, _variable_names: &[String]) -> Option<DataType> {
+        fn get_variable_type(&self, _variable_names: &[String]) -> Option<LogicalType> {
             None
         }
 
diff --git a/datafusion/sql/src/expr/value.rs b/datafusion/sql/src/expr/value.rs
index fa95fc2e051d..a9a2698397a9 100644
--- a/datafusion/sql/src/expr/value.rs
+++ b/datafusion/sql/src/expr/value.rs
@@ -18,7 +18,6 @@
 use crate::planner::{ContextProvider, PlannerContext, SqlToRel};
 use arrow::compute::kernels::cast_utils::parse_interval_month_day_nano;
 use arrow::datatypes::DECIMAL128_MAX_PRECISION;
-use arrow_schema::DataType;
 use datafusion_common::{
     not_impl_err, plan_err, DFSchema, DataFusionError, Result, ScalarValue,
 };
@@ -28,12 +27,13 @@ use log::debug;
 use sqlparser::ast::{BinaryOperator, Expr as SQLExpr, Interval, Value};
 use sqlparser::parser::ParserError::ParserError;
 use std::borrow::Cow;
+use datafusion_common::logical_type::LogicalType;
 
 impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     pub(crate) fn parse_value(
         &self,
         value: Value,
-        param_data_types: &[DataType],
+        param_data_types: &[LogicalType],
     ) -> Result<Expr> {
         match value {
             Value::Number(n, _) => self.parse_sql_number(&n, false),
@@ -96,7 +96,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     /// number 1, 2, ... etc. For example, `$1` is the first placeholder; $2 is the second one and so on.
     fn create_placeholder_expr(
         param: String,
-        param_data_types: &[DataType],
+        param_data_types: &[LogicalType],
     ) -> Result<Expr> {
         // Parse the placeholder as a number because it is the only support from sqlparser and postgres
         let index = param[1..].parse::<usize>();
diff --git a/datafusion/sql/src/planner.rs b/datafusion/sql/src/planner.rs
index 63ef86446aaf..a62eb2f126ad 100644
--- a/datafusion/sql/src/planner.rs
+++ b/datafusion/sql/src/planner.rs
@@ -37,6 +37,10 @@ use datafusion_common::{
     not_impl_err, plan_err, unqualified_field_not_found, DFSchema, DataFusionError,
     Result,
 };
+use datafusion_common::logical_type::field::LogicalField;
+use datafusion_common::logical_type::fields::LogicalFields;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 use datafusion_expr::logical_plan::{LogicalPlan, LogicalPlanBuilder};
 use datafusion_expr::utils::find_column_exprs;
 use datafusion_expr::TableSource;
@@ -83,7 +87,7 @@ pub trait ContextProvider {
     /// Getter for a UDWF
     fn get_window_meta(&self, name: &str) -> Option<Arc<WindowUDF>>;
     /// Getter for system/user-defined variable type
-    fn get_variable_type(&self, variable_names: &[String]) -> Option<DataType>;
+    fn get_variable_type(&self, variable_names: &[String]) -> Option<LogicalType>;
 
     /// Get configuration options
     fn options(&self) -> &ConfigOptions;
@@ -156,7 +160,7 @@ impl IdentNormalizer {
 pub struct PlannerContext {
     /// Data types for numbered parameters ($1, $2, etc), if supplied
     /// in `PREPARE` statement
-    prepare_param_data_types: Arc<Vec<DataType>>,
+    prepare_param_data_types: Arc<Vec<LogicalType>>,
     /// Map of CTE name to logical plan of the WITH clause.
     /// Use `Arc<LogicalPlan>` to allow cheap cloning
     ctes: HashMap<String, Arc<LogicalPlan>>,
@@ -183,7 +187,7 @@ impl PlannerContext {
     /// Update the PlannerContext with provided prepare_param_data_types
     pub fn with_prepare_param_data_types(
         mut self,
-        prepare_param_data_types: Vec<DataType>,
+        prepare_param_data_types: Vec<LogicalType>,
     ) -> Self {
         self.prepare_param_data_types = prepare_param_data_types.into();
         self
@@ -205,7 +209,7 @@ impl PlannerContext {
     }
 
     /// Return the types of parameters (`$1`, `$2`, etc) if known
-    pub fn prepare_param_data_types(&self) -> &[DataType] {
+    pub fn prepare_param_data_types(&self) -> &[LogicalType] {
         &self.prepare_param_data_types
     }
 
@@ -257,7 +261,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         }
     }
 
-    pub fn build_schema(&self, columns: Vec<SQLColumnDef>) -> Result<Schema> {
+    pub fn build_schema(&self, columns: Vec<SQLColumnDef>) -> Result<LogicalSchema> {
         let mut fields = Vec::with_capacity(columns.len());
 
         for column in columns {
@@ -266,14 +270,14 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                 .options
                 .iter()
                 .any(|x| x.option == ColumnOption::NotNull);
-            fields.push(Field::new(
+            fields.push(LogicalField::new(
                 self.normalizer.normalize(column.name),
                 data_type,
                 !not_nullable,
             ));
         }
 
-        Ok(Schema::new(fields))
+        Ok(LogicalSchema::new(fields))
     }
 
     /// Returns a vector of (column_name, default_expr) pairs
@@ -377,13 +381,13 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
             })
     }
 
-    pub(crate) fn convert_data_type(&self, sql_type: &SQLDataType) -> Result<DataType> {
+    pub(crate) fn convert_data_type(&self, sql_type: &SQLDataType) -> Result<LogicalType> {
         match sql_type {
             SQLDataType::Array(ArrayElemTypeDef::AngleBracket(inner_sql_type))
             | SQLDataType::Array(ArrayElemTypeDef::SquareBracket(inner_sql_type, _)) => {
                 // Arrays may be multi-dimensional.
                 let inner_data_type = self.convert_data_type(inner_sql_type)?;
-                Ok(DataType::new_list(inner_data_type, true))
+                Ok(LogicalType::new_list(inner_data_type, true).into())
             }
             SQLDataType::Array(ArrayElemTypeDef::None) => {
                 not_impl_err!("Arrays with unspecified type is not supported")
@@ -392,26 +396,26 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         }
     }
 
-    fn convert_simple_data_type(&self, sql_type: &SQLDataType) -> Result<DataType> {
+    fn convert_simple_data_type(&self, sql_type: &SQLDataType) -> Result<LogicalType> {
         match sql_type {
-            SQLDataType::Boolean | SQLDataType::Bool => Ok(DataType::Boolean),
-            SQLDataType::TinyInt(_) => Ok(DataType::Int8),
-            SQLDataType::SmallInt(_) | SQLDataType::Int2(_) => Ok(DataType::Int16),
-            SQLDataType::Int(_) | SQLDataType::Integer(_) | SQLDataType::Int4(_) => Ok(DataType::Int32),
-            SQLDataType::BigInt(_) | SQLDataType::Int8(_) => Ok(DataType::Int64),
-            SQLDataType::UnsignedTinyInt(_) => Ok(DataType::UInt8),
-            SQLDataType::UnsignedSmallInt(_) | SQLDataType::UnsignedInt2(_) => Ok(DataType::UInt16),
+            SQLDataType::Boolean | SQLDataType::Bool => Ok(LogicalType::Boolean),
+            SQLDataType::TinyInt(_) => Ok(LogicalType::Int8),
+            SQLDataType::SmallInt(_) | SQLDataType::Int2(_) => Ok(LogicalType::Int16),
+            SQLDataType::Int(_) | SQLDataType::Integer(_) | SQLDataType::Int4(_) => Ok(LogicalType::Int32),
+            SQLDataType::BigInt(_) | SQLDataType::Int8(_) => Ok(LogicalType::Int64),
+            SQLDataType::UnsignedTinyInt(_) => Ok(LogicalType::UInt8),
+            SQLDataType::UnsignedSmallInt(_) | SQLDataType::UnsignedInt2(_) => Ok(LogicalType::UInt16),
             SQLDataType::UnsignedInt(_) | SQLDataType::UnsignedInteger(_) | SQLDataType::UnsignedInt4(_) => {
-                Ok(DataType::UInt32)
+                Ok(LogicalType::UInt32)
             }
-            SQLDataType::UnsignedBigInt(_) | SQLDataType::UnsignedInt8(_) => Ok(DataType::UInt64),
-            SQLDataType::Float(_) => Ok(DataType::Float32),
-            SQLDataType::Real | SQLDataType::Float4 => Ok(DataType::Float32),
-            SQLDataType::Double | SQLDataType::DoublePrecision | SQLDataType::Float8 => Ok(DataType::Float64),
+            SQLDataType::UnsignedBigInt(_) | SQLDataType::UnsignedInt8(_) => Ok(LogicalType::UInt64),
+            SQLDataType::Float(_) => Ok(LogicalType::Float32),
+            SQLDataType::Real | SQLDataType::Float4 => Ok(LogicalType::Float32),
+            SQLDataType::Double | SQLDataType::DoublePrecision | SQLDataType::Float8 => Ok(LogicalType::Float64),
             SQLDataType::Char(_)
             | SQLDataType::Varchar(_)
             | SQLDataType::Text
-            | SQLDataType::String(_) => Ok(DataType::Utf8),
+            | SQLDataType::String(_) => Ok(LogicalType::Utf8),
             SQLDataType::Timestamp(None, tz_info) => {
                 let tz = if matches!(tz_info, TimezoneInfo::Tz)
                     || matches!(tz_info, TimezoneInfo::WithTimeZone)
@@ -424,14 +428,14 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                     // Timestamp Without Time zone
                     None
                 };
-                Ok(DataType::Timestamp(TimeUnit::Nanosecond, tz.map(Into::into)))
+                Ok(LogicalType::Timestamp(TimeUnit::Nanosecond, tz.map(Into::into)))
             }
-            SQLDataType::Date => Ok(DataType::Date32),
+            SQLDataType::Date => Ok(LogicalType::Date32),
             SQLDataType::Time(None, tz_info) => {
                 if matches!(tz_info, TimezoneInfo::None)
                     || matches!(tz_info, TimezoneInfo::WithoutTimeZone)
                 {
-                    Ok(DataType::Time64(TimeUnit::Nanosecond))
+                    Ok(LogicalType::Time64(TimeUnit::Nanosecond))
                 } else {
                     // We dont support TIMETZ and TIME WITH TIME ZONE for now
                     not_impl_err!(
@@ -450,8 +454,8 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                 };
                 make_decimal_type(precision, scale)
             }
-            SQLDataType::Bytea => Ok(DataType::Binary),
-            SQLDataType::Interval => Ok(DataType::Interval(IntervalUnit::MonthDayNano)),
+            SQLDataType::Bytea => Ok(LogicalType::Binary),
+            SQLDataType::Interval => Ok(LogicalType::Interval(IntervalUnit::MonthDayNano)),
             SQLDataType::Struct(fields) => {
                 let fields = fields
                     .iter()
@@ -462,14 +466,14 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                             Some(ident) => ident.clone(),
                             None => Ident::new(format!("c{idx}"))
                         };
-                        Ok(Arc::new(Field::new(
+                        Ok(Arc::new(LogicalField::new(
                             self.normalizer.normalize(field_name),
                             data_type,
                             true,
                         )))
                     })
                     .collect::<Result<Vec<_>>>()?;
-                Ok(DataType::Struct(Fields::from(fields)))
+                Ok(LogicalType::Struct(LogicalFields::from(fields)))
             }
             // Explicitly list all other types so that if sqlparser
             // adds/changes the `SQLDataType` the compiler will tell us on upgrade
diff --git a/datafusion/sql/src/relation/join.rs b/datafusion/sql/src/relation/join.rs
index ee2e35b550f6..8978cb10b768 100644
--- a/datafusion/sql/src/relation/join.rs
+++ b/datafusion/sql/src/relation/join.rs
@@ -122,7 +122,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                     .build()
             }
             JoinConstraint::Natural => {
-                let left_cols: HashSet<&String> =
+                let left_cols: HashSet<&str> =
                     left.schema().fields().iter().map(|f| f.name()).collect();
                 let keys: Vec<Column> = right
                     .schema()
diff --git a/datafusion/sql/src/statement.rs b/datafusion/sql/src/statement.rs
index 518972545a48..4e61f38b4abf 100644
--- a/datafusion/sql/src/statement.rs
+++ b/datafusion/sql/src/statement.rs
@@ -29,7 +29,6 @@ use crate::planner::{
 };
 use crate::utils::normalize_ident;
 
-use arrow_schema::{DataType, Fields};
 use datafusion_common::parsers::CompressionTypeVariant;
 use datafusion_common::{
     exec_err, not_impl_err, plan_datafusion_err, plan_err, schema_err,
@@ -60,6 +59,9 @@ use sqlparser::ast::{
     TableConstraint, TableFactor, TableWithJoins, TransactionMode, UnaryOperator, Value,
 };
 use sqlparser::parser::ParserError::ParserError;
+use datafusion_common::logical_type::fields::LogicalFields;
+use datafusion_common::logical_type::LogicalType;
+use datafusion_common::logical_type::schema::LogicalSchema;
 
 fn ident_to_string(ident: &Ident) -> String {
     normalize_ident(ident.to_owned())
@@ -453,7 +455,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                 statement,
             } => {
                 // Convert parser data types to DataFusion data types
-                let data_types: Vec<DataType> = data_types
+                let data_types: Vec<LogicalType> = data_types
                     .into_iter()
                     .map(|t| self.convert_data_type(&t))
                     .collect::<Result<_>>()?;
@@ -1222,7 +1224,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         // Do a table lookup to verify the table exists
         let table_ref = self.object_name_to_table_reference(table_name.clone())?;
         let table_source = self.context_provider.get_table_source(table_ref.clone())?;
-        let schema = (*table_source.schema()).clone();
+        let schema: LogicalSchema = (*table_source.schema()).clone().into();
         let schema = DFSchema::try_from(schema)?;
         let scan = LogicalPlanBuilder::scan(
             object_name_to_string(&table_name),
@@ -1275,7 +1277,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         let table_source = self.context_provider.get_table_source(table_name.clone())?;
         let table_schema = Arc::new(DFSchema::try_from_qualified_schema(
             table_name.clone(),
-            &table_source.schema(),
+            &table_source.schema().as_ref().clone().into(),
         )?);
 
         // Overwrite with assignment expressions
@@ -1380,7 +1382,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         // Do a table lookup to verify the table exists
         let table_name = self.object_name_to_table_reference(table_name)?;
         let table_source = self.context_provider.get_table_source(table_name.clone())?;
-        let arrow_schema = (*table_source.schema()).clone();
+        let arrow_schema: LogicalSchema = (*table_source.schema()).clone().into();
         let table_schema = DFSchema::try_from(arrow_schema)?;
 
         // Get insert fields and target table's value indices
@@ -1418,7 +1420,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                     Ok(table_schema.field(column_index).clone())
                 })
                 .collect::<Result<Vec<_>>>()?;
-            (Fields::from(fields), value_indices)
+            (LogicalFields::from(fields), value_indices)
         };
 
         // infer types for Values clause... other types should be resolvable the regular way
diff --git a/datafusion/sql/src/unparser/expr.rs b/datafusion/sql/src/unparser/expr.rs
index ad898de5987a..33186312ac0c 100644
--- a/datafusion/sql/src/unparser/expr.rs
+++ b/datafusion/sql/src/unparser/expr.rs
@@ -27,7 +27,6 @@ use arrow_array::types::{
     TimestampNanosecondType, TimestampSecondType,
 };
 use arrow_array::{Date32Array, Date64Array, PrimitiveArray};
-use arrow_schema::DataType;
 use sqlparser::ast::Value::SingleQuotedString;
 use sqlparser::ast::{
     self, Expr as AstExpr, Function, FunctionArg, Ident, Interval, TimezoneInfo,
@@ -38,6 +37,7 @@ use datafusion_common::{
     internal_datafusion_err, internal_err, not_impl_err, plan_err, Column, Result,
     ScalarValue,
 };
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::{
     expr::{Alias, Exists, InList, ScalarFunction, Sort, WindowFunction},
     Between, BinaryExpr, Case, Cast, Expr, GroupingSet, Like, Operator, TryCast,
@@ -957,85 +957,67 @@ impl Unparser<'_> {
         }
     }
 
-    fn arrow_dtype_to_ast_dtype(&self, data_type: &DataType) -> Result<ast::DataType> {
+    fn arrow_dtype_to_ast_dtype(&self, data_type: &LogicalType) -> Result<ast::DataType> {
         match data_type {
-            DataType::Null => {
+            LogicalType::Null => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Boolean => Ok(ast::DataType::Bool),
-            DataType::Int8 => Ok(ast::DataType::TinyInt(None)),
-            DataType::Int16 => Ok(ast::DataType::SmallInt(None)),
-            DataType::Int32 => Ok(ast::DataType::Integer(None)),
-            DataType::Int64 => Ok(ast::DataType::BigInt(None)),
-            DataType::UInt8 => Ok(ast::DataType::UnsignedTinyInt(None)),
-            DataType::UInt16 => Ok(ast::DataType::UnsignedSmallInt(None)),
-            DataType::UInt32 => Ok(ast::DataType::UnsignedInteger(None)),
-            DataType::UInt64 => Ok(ast::DataType::UnsignedBigInt(None)),
-            DataType::Float16 => {
+            LogicalType::Boolean => Ok(ast::DataType::Bool),
+            LogicalType::Int8 => Ok(ast::DataType::TinyInt(None)),
+            LogicalType::Int16 => Ok(ast::DataType::SmallInt(None)),
+            LogicalType::Int32 => Ok(ast::DataType::Integer(None)),
+            LogicalType::Int64 => Ok(ast::DataType::BigInt(None)),
+            LogicalType::UInt8 => Ok(ast::DataType::UnsignedTinyInt(None)),
+            LogicalType::UInt16 => Ok(ast::DataType::UnsignedSmallInt(None)),
+            LogicalType::UInt32 => Ok(ast::DataType::UnsignedInteger(None)),
+            LogicalType::UInt64 => Ok(ast::DataType::UnsignedBigInt(None)),
+            LogicalType::Float16 => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Float32 => Ok(ast::DataType::Float(None)),
-            DataType::Float64 => Ok(ast::DataType::Double),
-            DataType::Timestamp(_, _) => {
+            LogicalType::Float32 => Ok(ast::DataType::Float(None)),
+            LogicalType::Float64 => Ok(ast::DataType::Double),
+            LogicalType::Timestamp(_, _) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Date32 => Ok(ast::DataType::Date),
-            DataType::Date64 => Ok(ast::DataType::Datetime(None)),
-            DataType::Time32(_) => {
+            LogicalType::Date32 => Ok(ast::DataType::Date),
+            LogicalType::Date64 => Ok(ast::DataType::Datetime(None)),
+            LogicalType::Time32(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Time64(_) => {
+            LogicalType::Time64(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Duration(_) => {
+            LogicalType::Duration(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Interval(_) => {
+            LogicalType::Interval(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Binary => {
+            LogicalType::Binary => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::FixedSizeBinary(_) => {
+            LogicalType::FixedSizeBinary(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::LargeBinary => {
+            LogicalType::LargeBinary => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::BinaryView => {
+            LogicalType::Utf8 => Ok(ast::DataType::Varchar(None)),
+            LogicalType::LargeUtf8 => Ok(ast::DataType::Text),
+            LogicalType::List(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::Utf8 => Ok(ast::DataType::Varchar(None)),
-            DataType::LargeUtf8 => Ok(ast::DataType::Text),
-            DataType::Utf8View => {
+            LogicalType::FixedSizeList(_, _) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::List(_) => {
+            LogicalType::LargeList(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::FixedSizeList(_, _) => {
+            LogicalType::Struct(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::LargeList(_) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::ListView(_) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::LargeListView(_) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::Struct(_) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::Union(_, _) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::Dictionary(_, _) => {
-                not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
-            }
-            DataType::Decimal128(precision, scale)
-            | DataType::Decimal256(precision, scale) => {
+            LogicalType::Decimal128(precision, scale)
+            | LogicalType::Decimal256(precision, scale) => {
                 let mut new_precision = *precision as u64;
                 let mut new_scale = *scale as u64;
                 if *scale < 0 {
@@ -1047,10 +1029,10 @@ impl Unparser<'_> {
                     ast::ExactNumberInfo::PrecisionAndScale(new_precision, new_scale),
                 ))
             }
-            DataType::Map(_, _) => {
+            LogicalType::Map(_, _) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
-            DataType::RunEndEncoded(_, _) => {
+            LogicalType::Extension(_) => {
                 not_impl_err!("Unsupported DataType: conversion: {data_type:?}")
             }
         }
@@ -1063,8 +1045,7 @@ mod tests {
     use std::{any::Any, sync::Arc, vec};
 
     use arrow::datatypes::{Field, Schema};
-    use arrow_schema::DataType::Int8;
-
+    use arrow_schema::DataType;
     use datafusion_common::TableReference;
     use datafusion_expr::{
         case, col, cube, exists, grouping_set, interval_datetime_lit,
@@ -1153,14 +1134,14 @@ mod tests {
             (
                 Expr::Cast(Cast {
                     expr: Box::new(col("a")),
-                    data_type: DataType::Date64,
+                    data_type: LogicalType::Date64,
                 }),
                 r#"CAST(a AS DATETIME)"#,
             ),
             (
                 Expr::Cast(Cast {
                     expr: Box::new(col("a")),
-                    data_type: DataType::UInt32,
+                    data_type: LogicalType::UInt32,
                 }),
                 r#"CAST(a AS INTEGER UNSIGNED)"#,
             ),
@@ -1386,27 +1367,27 @@ mod tests {
                 r#"NOT EXISTS (SELECT t.a FROM t WHERE (t.a = 1))"#,
             ),
             (
-                try_cast(col("a"), DataType::Date64),
+                try_cast(col("a"), LogicalType::Date64),
                 r#"TRY_CAST(a AS DATETIME)"#,
             ),
             (
-                try_cast(col("a"), DataType::UInt32),
+                try_cast(col("a"), LogicalType::UInt32),
                 r#"TRY_CAST(a AS INTEGER UNSIGNED)"#,
             ),
             (
-                Expr::ScalarVariable(Int8, vec![String::from("@a")]),
+                Expr::ScalarVariable(LogicalType::Int8, vec![String::from("@a")]),
                 r#"@a"#,
             ),
             (
                 Expr::ScalarVariable(
-                    Int8,
+                    LogicalType::Int8,
                     vec![String::from("@root"), String::from("foo")],
                 ),
                 r#"@root.foo"#,
             ),
             (col("x").eq(placeholder("$1")), r#"(x = $1)"#),
             (
-                out_ref_col(DataType::Int32, "t.a").gt(lit(1)),
+                out_ref_col(LogicalType::Int32, "t.a").gt(lit(1)),
                 r#"(t.a > 1)"#,
             ),
             (
@@ -1481,7 +1462,7 @@ mod tests {
             (
                 Expr::Cast(Cast {
                     expr: Box::new(col("a")),
-                    data_type: DataType::Decimal128(10, -2),
+                    data_type: LogicalType::Decimal128(10, -2),
                 }),
                 r#"CAST(a AS DECIMAL(12,0))"#,
             ),
diff --git a/datafusion/sql/src/utils.rs b/datafusion/sql/src/utils.rs
index bc27d25cf216..fbe8cd099f2a 100644
--- a/datafusion/sql/src/utils.rs
+++ b/datafusion/sql/src/utils.rs
@@ -20,7 +20,7 @@
 use std::collections::HashMap;
 
 use arrow_schema::{
-    DataType, DECIMAL128_MAX_PRECISION, DECIMAL256_MAX_PRECISION, DECIMAL_DEFAULT_SCALE,
+    DECIMAL128_MAX_PRECISION, DECIMAL256_MAX_PRECISION, DECIMAL_DEFAULT_SCALE,
 };
 use datafusion_common::tree_node::{Transformed, TransformedResult, TreeNode};
 use datafusion_common::{
@@ -31,6 +31,7 @@ use datafusion_expr::expr::{Alias, GroupingSet, Unnest, WindowFunction};
 use datafusion_expr::utils::{expr_as_column_expr, find_column_exprs};
 use datafusion_expr::{expr_vec_fmt, Expr, ExprSchemable, LogicalPlan};
 use sqlparser::ast::Ident;
+use datafusion_common::logical_type::LogicalType;
 
 /// Make a best-effort attempt at resolving all columns in the expression tree
 pub(crate) fn resolve_columns(expr: &Expr, plan: &LogicalPlan) -> Result<Expr> {
@@ -226,7 +227,7 @@ pub fn window_expr_common_partition_keys(window_exprs: &[Expr]) -> Result<&[Expr
 pub(crate) fn make_decimal_type(
     precision: Option<u64>,
     scale: Option<u64>,
-) -> Result<DataType> {
+) -> Result<LogicalType> {
     // postgres like behavior
     let (precision, scale) = match (precision, scale) {
         (Some(p), Some(s)) => (p as u8, s as i8),
@@ -247,9 +248,9 @@ pub(crate) fn make_decimal_type(
     } else if precision > DECIMAL128_MAX_PRECISION
         && precision <= DECIMAL256_MAX_PRECISION
     {
-        Ok(DataType::Decimal256(precision, scale))
+        Ok(LogicalType::Decimal256(precision, scale))
     } else {
-        Ok(DataType::Decimal128(precision, scale))
+        Ok(LogicalType::Decimal128(precision, scale))
     }
 }
 
@@ -316,7 +317,7 @@ pub(crate) fn recursive_transform_unnest(
         } = original_expr.transform_up(|expr: Expr| {
             if let Expr::Unnest(Unnest { expr: ref arg }) = expr {
                 let (data_type, _) = arg.data_type_and_nullable(input.schema())?;
-                if let DataType::Struct(_) = data_type {
+                if let LogicalType::Struct(_) = data_type {
                     return internal_err!("unnest on struct can ony be applied at the root level of select expression");
                 }
                 let transformed_exprs = transform(&expr, arg)?;
diff --git a/datafusion/sql/tests/cases/plan_to_sql.rs b/datafusion/sql/tests/cases/plan_to_sql.rs
index 374403d853f9..eefa9e2b3471 100644
--- a/datafusion/sql/tests/cases/plan_to_sql.rs
+++ b/datafusion/sql/tests/cases/plan_to_sql.rs
@@ -30,7 +30,6 @@ use datafusion_sql::unparser::{expr_to_sql, plan_to_sql, Unparser};
 
 use sqlparser::dialect::{Dialect, GenericDialect, MySqlDialect};
 use sqlparser::parser::Parser;
-
 use crate::common::MockContextProvider;
 
 #[test]
diff --git a/datafusion/sql/tests/common/mod.rs b/datafusion/sql/tests/common/mod.rs
index f5caaefb3ea0..d7124d5e0180 100644
--- a/datafusion/sql/tests/common/mod.rs
+++ b/datafusion/sql/tests/common/mod.rs
@@ -25,6 +25,7 @@ use arrow_schema::*;
 use datafusion_common::config::ConfigOptions;
 use datafusion_common::file_options::file_type::FileType;
 use datafusion_common::{plan_err, GetExt, Result, TableReference};
+use datafusion_common::logical_type::LogicalType;
 use datafusion_expr::{AggregateUDF, ScalarUDF, TableSource, WindowUDF};
 use datafusion_sql::planner::ContextProvider;
 
@@ -202,7 +203,7 @@ impl ContextProvider for MockContextProvider {
         self.udafs.get(name).cloned()
     }
 
-    fn get_variable_type(&self, _: &[String]) -> Option<DataType> {
+    fn get_variable_type(&self, _: &[String]) -> Option<LogicalType> {
         unimplemented!()
     }
 
diff --git a/datafusion/sql/tests/sql_integration.rs b/datafusion/sql/tests/sql_integration.rs
index f196d71d41de..777c935e2bfd 100644
--- a/datafusion/sql/tests/sql_integration.rs
+++ b/datafusion/sql/tests/sql_integration.rs
@@ -43,6 +43,7 @@ use datafusion_functions_aggregate::{
 };
 use rstest::rstest;
 use sqlparser::dialect::{Dialect, GenericDialect, HiveDialect, MySqlDialect};
+use datafusion_common::logical_type::LogicalType;
 
 mod cases;
 mod common;
@@ -3660,8 +3661,8 @@ fn test_prepare_statement_should_infer_types() {
     let plan = logical_plan(sql).unwrap();
     let actual_types = plan.get_parameter_types().unwrap();
     let expected_types = HashMap::from([
-        ("$1".to_string(), Some(DataType::Int32)),
-        ("$2".to_string(), Some(DataType::Int64)),
+        ("$1".to_string(), Some(LogicalType::Int32)),
+        ("$2".to_string(), Some(LogicalType::Int64)),
     ]);
     assert_eq!(actual_types, expected_types);
 }
@@ -3674,7 +3675,7 @@ fn test_non_prepare_statement_should_infer_types() {
     let actual_types = plan.get_parameter_types().unwrap();
     let expected_types = HashMap::from([
         // constant 1 is inferred to be int64
-        ("$1".to_string(), Some(DataType::Int64)),
+        ("$1".to_string(), Some(LogicalType::Int64)),
     ]);
     assert_eq!(actual_types, expected_types);
 }
@@ -3849,7 +3850,7 @@ Projection: person.id, orders.order_id
     let plan = prepare_stmt_quick_test(sql, expected_plan, expected_dt);
 
     let actual_types = plan.get_parameter_types().unwrap();
-    let expected_types = HashMap::from([("$1".to_string(), Some(DataType::Int32))]);
+    let expected_types = HashMap::from([("$1".to_string(), Some(LogicalType::Int32))]);
     assert_eq!(actual_types, expected_types);
 
     // replace params with values
@@ -3881,7 +3882,7 @@ Projection: person.id, person.age
     let plan = prepare_stmt_quick_test(sql, expected_plan, expected_dt);
 
     let actual_types = plan.get_parameter_types().unwrap();
-    let expected_types = HashMap::from([("$1".to_string(), Some(DataType::Int32))]);
+    let expected_types = HashMap::from([("$1".to_string(), Some(LogicalType::Int32))]);
     assert_eq!(actual_types, expected_types);
 
     // replace params with values
@@ -3913,8 +3914,8 @@ Projection: person.id, person.age
 
     let actual_types = plan.get_parameter_types().unwrap();
     let expected_types = HashMap::from([
-        ("$1".to_string(), Some(DataType::Int32)),
-        ("$2".to_string(), Some(DataType::Int32)),
+        ("$1".to_string(), Some(LogicalType::Int32)),
+        ("$2".to_string(), Some(LogicalType::Int32)),
     ]);
     assert_eq!(actual_types, expected_types);
 
@@ -3952,7 +3953,7 @@ Projection: person.id, person.age
     let plan = prepare_stmt_quick_test(sql, expected_plan, expected_dt);
 
     let actual_types = plan.get_parameter_types().unwrap();
-    let expected_types = HashMap::from([("$1".to_string(), Some(DataType::UInt32))]);
+    let expected_types = HashMap::from([("$1".to_string(), Some(LogicalType::UInt32))]);
     assert_eq!(actual_types, expected_types);
 
     // replace params with values
@@ -3990,8 +3991,8 @@ Dml: op=[Update] table=[person]
 
     let actual_types = plan.get_parameter_types().unwrap();
     let expected_types = HashMap::from([
-        ("$1".to_string(), Some(DataType::Int32)),
-        ("$2".to_string(), Some(DataType::UInt32)),
+        ("$1".to_string(), Some(LogicalType::Int32)),
+        ("$2".to_string(), Some(LogicalType::UInt32)),
     ]);
     assert_eq!(actual_types, expected_types);
 
@@ -4025,9 +4026,9 @@ fn test_prepare_statement_insert_infer() {
 
     let actual_types = plan.get_parameter_types().unwrap();
     let expected_types = HashMap::from([
-        ("$1".to_string(), Some(DataType::UInt32)),
-        ("$2".to_string(), Some(DataType::Utf8)),
-        ("$3".to_string(), Some(DataType::Utf8)),
+        ("$1".to_string(), Some(LogicalType::UInt32)),
+        ("$2".to_string(), Some(LogicalType::Utf8)),
+        ("$3".to_string(), Some(LogicalType::Utf8)),
     ]);
     assert_eq!(actual_types, expected_types);
 
diff --git a/datafusion/sqllogictest/src/engines/datafusion_engine/normalize.rs b/datafusion/sqllogictest/src/engines/datafusion_engine/normalize.rs
index 520b6b53b32d..3dfcb34d1a3e 100644
--- a/datafusion/sqllogictest/src/engines/datafusion_engine/normalize.rs
+++ b/datafusion/sqllogictest/src/engines/datafusion_engine/normalize.rs
@@ -15,10 +15,11 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use arrow::datatypes::Fields;
 use arrow::util::display::ArrayFormatter;
 use arrow::{array, array::ArrayRef, datatypes::DataType, record_batch::RecordBatch};
 use datafusion_common::format::DEFAULT_FORMAT_OPTIONS;
+use datafusion_common::logical_type::fields::LogicalFields;
+use datafusion_common::logical_type::LogicalType;
 use datafusion_common::DataFusionError;
 use std::path::PathBuf;
 use std::sync::OnceLock;
@@ -243,31 +244,31 @@ pub fn cell_to_string(col: &ArrayRef, row: usize) -> Result<String> {
 }
 
 /// Converts columns to a result as expected by sqllogicteset.
-pub(crate) fn convert_schema_to_types(columns: &Fields) -> Vec<DFColumnType> {
+pub(crate) fn convert_schema_to_types(columns: &LogicalFields) -> Vec<DFColumnType> {
     columns
         .iter()
         .map(|f| f.data_type())
         .map(|data_type| match data_type {
-            DataType::Boolean => DFColumnType::Boolean,
-            DataType::Int8
-            | DataType::Int16
-            | DataType::Int32
-            | DataType::Int64
-            | DataType::UInt8
-            | DataType::UInt16
-            | DataType::UInt32
-            | DataType::UInt64 => DFColumnType::Integer,
-            DataType::Float16
-            | DataType::Float32
-            | DataType::Float64
-            | DataType::Decimal128(_, _)
-            | DataType::Decimal256(_, _) => DFColumnType::Float,
-            DataType::Utf8 | DataType::LargeUtf8 => DFColumnType::Text,
-            DataType::Date32
-            | DataType::Date64
-            | DataType::Time32(_)
-            | DataType::Time64(_) => DFColumnType::DateTime,
-            DataType::Timestamp(_, _) => DFColumnType::Timestamp,
+            LogicalType::Boolean => DFColumnType::Boolean,
+            LogicalType::Int8
+            | LogicalType::Int16
+            | LogicalType::Int32
+            | LogicalType::Int64
+            | LogicalType::UInt8
+            | LogicalType::UInt16
+            | LogicalType::UInt32
+            | LogicalType::UInt64 => DFColumnType::Integer,
+            LogicalType::Float16
+            | LogicalType::Float32
+            | LogicalType::Float64
+            | LogicalType::Decimal128(_, _)
+            | LogicalType::Decimal256(_, _) => DFColumnType::Float,
+            LogicalType::Utf8 | LogicalType::LargeUtf8 => DFColumnType::Text,
+            LogicalType::Date32
+            | LogicalType::Date64
+            | LogicalType::Time32(_)
+            | LogicalType::Time64(_) => DFColumnType::DateTime,
+            LogicalType::Timestamp(_, _) => DFColumnType::Timestamp,
             _ => DFColumnType::Another,
         })
         .collect()
diff --git a/datafusion/substrait/src/logical_plan/consumer.rs b/datafusion/substrait/src/logical_plan/consumer.rs
index 9bc842a12af4..56f659f1d870 100644
--- a/datafusion/substrait/src/logical_plan/consumer.rs
+++ b/datafusion/substrait/src/logical_plan/consumer.rs
@@ -17,8 +17,13 @@
 
 use async_recursion::async_recursion;
 use datafusion::arrow::datatypes::{
-    DataType, Field, FieldRef, Fields, IntervalUnit, Schema, TimeUnit,
+    Field, FieldRef, Fields, IntervalUnit, Schema, TimeUnit,
 };
+use datafusion::common::logical_type::extension::ExtensionType;
+use datafusion::common::logical_type::field::{LogicalField, LogicalFieldRef};
+use datafusion::common::logical_type::fields::LogicalFields;
+use datafusion::common::logical_type::schema::LogicalSchema;
+use datafusion::common::logical_type::LogicalType;
 use datafusion::common::{
     not_impl_err, substrait_datafusion_err, substrait_err, DFSchema, DFSchemaRef,
 };
@@ -349,12 +354,12 @@ fn make_renamed_schema(
     dfs_names: &Vec<String>,
 ) -> Result<DFSchema> {
     fn rename_inner_fields(
-        dtype: &DataType,
+        dtype: &LogicalType,
         dfs_names: &Vec<String>,
         name_idx: &mut usize,
-    ) -> Result<DataType> {
+    ) -> Result<LogicalType> {
         match dtype {
-            DataType::Struct(fields) => {
+            LogicalType::Struct(fields) => {
                 let fields = fields
                     .iter()
                     .map(|f| {
@@ -364,16 +369,16 @@ fn make_renamed_schema(
                         ))
                     })
                     .collect::<Result<_>>()?;
-                Ok(DataType::Struct(fields))
+                Ok(LogicalType::Struct(fields))
             }
-            DataType::List(inner) => Ok(DataType::List(FieldRef::new(
+            LogicalType::List(inner) => Ok(LogicalType::List(LogicalFieldRef::new(
                 (**inner).to_owned().with_data_type(rename_inner_fields(
                     inner.data_type(),
                     dfs_names,
                     name_idx,
                 )?),
             ))),
-            DataType::LargeList(inner) => Ok(DataType::LargeList(FieldRef::new(
+            LogicalType::LargeList(inner) => Ok(LogicalType::LargeList(LogicalFieldRef::new(
                 (**inner).to_owned().with_data_type(rename_inner_fields(
                     inner.data_type(),
                     dfs_names,
@@ -386,7 +391,7 @@ fn make_renamed_schema(
 
     let mut name_idx = 0;
 
-    let (qualifiers, fields): (_, Vec<Field>) = schema
+    let (qualifiers, fields): (_, Vec<LogicalField>) = schema
         .iter()
         .map(|(q, f)| {
             let name = next_struct_field_name(0, dfs_names, &mut name_idx)?;
@@ -415,7 +420,7 @@ fn make_renamed_schema(
 
     DFSchema::from_field_specific_qualified_schema(
         qualifiers,
-        &Arc::new(Schema::new(fields)),
+        &Arc::new(LogicalSchema::new(fields)),
     )
 }
 
@@ -863,7 +868,7 @@ pub async fn from_substrait_rel(
 }
 
 /// (Re)qualify the sides of a join if needed, i.e. if the columns from one side would otherwise
-/// conflict with the columns from the other.  
+/// conflict with the columns from the other.
 /// Substrait doesn't currently allow specifying aliases, neither for columns nor for tables. For
 /// Substrait the names don't matter since it only refers to columns by indices, however DataFusion
 /// requires columns to be uniquely identifiable, in some places (see e.g. DFSchema::check_names).
@@ -1348,7 +1353,7 @@ pub async fn from_substrait_rex(
     }
 }
 
-pub(crate) fn from_substrait_type_without_names(dt: &Type) -> Result<DataType> {
+pub(crate) fn from_substrait_type_without_names(dt: &Type) -> Result<LogicalType> {
     from_substrait_type(dt, &[], &mut 0)
 }
 
@@ -1356,77 +1361,77 @@ fn from_substrait_type(
     dt: &Type,
     dfs_names: &[String],
     name_idx: &mut usize,
-) -> Result<DataType> {
+) -> Result<LogicalType> {
     match &dt.kind {
         Some(s_kind) => match s_kind {
-            r#type::Kind::Bool(_) => Ok(DataType::Boolean),
+            r#type::Kind::Bool(_) => Ok(LogicalType::Boolean),
             r#type::Kind::I8(integer) => match integer.type_variation_reference {
-                DEFAULT_TYPE_VARIATION_REF => Ok(DataType::Int8),
-                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(DataType::UInt8),
+                DEFAULT_TYPE_VARIATION_REF => Ok(LogicalType::Int8),
+                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(LogicalType::UInt8),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::I16(integer) => match integer.type_variation_reference {
-                DEFAULT_TYPE_VARIATION_REF => Ok(DataType::Int16),
-                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(DataType::UInt16),
+                DEFAULT_TYPE_VARIATION_REF => Ok(LogicalType::Int16),
+                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(LogicalType::UInt16),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::I32(integer) => match integer.type_variation_reference {
-                DEFAULT_TYPE_VARIATION_REF => Ok(DataType::Int32),
-                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(DataType::UInt32),
+                DEFAULT_TYPE_VARIATION_REF => Ok(LogicalType::Int32),
+                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(LogicalType::UInt32),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::I64(integer) => match integer.type_variation_reference {
-                DEFAULT_TYPE_VARIATION_REF => Ok(DataType::Int64),
-                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(DataType::UInt64),
+                DEFAULT_TYPE_VARIATION_REF => Ok(LogicalType::Int64),
+                UNSIGNED_INTEGER_TYPE_VARIATION_REF => Ok(LogicalType::UInt64),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
-            r#type::Kind::Fp32(_) => Ok(DataType::Float32),
-            r#type::Kind::Fp64(_) => Ok(DataType::Float64),
+            r#type::Kind::Fp32(_) => Ok(LogicalType::Float32),
+            r#type::Kind::Fp64(_) => Ok(LogicalType::Float64),
             r#type::Kind::Timestamp(ts) => match ts.type_variation_reference {
                 TIMESTAMP_SECOND_TYPE_VARIATION_REF => {
-                    Ok(DataType::Timestamp(TimeUnit::Second, None))
+                    Ok(LogicalType::Timestamp(TimeUnit::Second, None))
                 }
                 TIMESTAMP_MILLI_TYPE_VARIATION_REF => {
-                    Ok(DataType::Timestamp(TimeUnit::Millisecond, None))
+                    Ok(LogicalType::Timestamp(TimeUnit::Millisecond, None))
                 }
                 TIMESTAMP_MICRO_TYPE_VARIATION_REF => {
-                    Ok(DataType::Timestamp(TimeUnit::Microsecond, None))
+                    Ok(LogicalType::Timestamp(TimeUnit::Microsecond, None))
                 }
                 TIMESTAMP_NANO_TYPE_VARIATION_REF => {
-                    Ok(DataType::Timestamp(TimeUnit::Nanosecond, None))
+                    Ok(LogicalType::Timestamp(TimeUnit::Nanosecond, None))
                 }
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::Date(date) => match date.type_variation_reference {
-                DATE_32_TYPE_VARIATION_REF => Ok(DataType::Date32),
-                DATE_64_TYPE_VARIATION_REF => Ok(DataType::Date64),
+                DATE_32_TYPE_VARIATION_REF => Ok(LogicalType::Date32),
+                DATE_64_TYPE_VARIATION_REF => Ok(LogicalType::Date64),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::Binary(binary) => match binary.type_variation_reference {
-                DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::Binary),
-                LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::LargeBinary),
+                DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::Binary),
+                LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::LargeBinary),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
             },
             r#type::Kind::FixedBinary(fixed) => {
-                Ok(DataType::FixedSizeBinary(fixed.length))
+                Ok(LogicalType::FixedSizeBinary(fixed.length))
             }
             r#type::Kind::String(string) => match string.type_variation_reference {
-                DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::Utf8),
-                LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::LargeUtf8),
+                DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::Utf8),
+                LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::LargeUtf8),
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
                 ),
@@ -1435,15 +1440,15 @@ fn from_substrait_type(
                 let inner_type = list.r#type.as_ref().ok_or_else(|| {
                     substrait_datafusion_err!("List type must have inner type")
                 })?;
-                let field = Arc::new(Field::new_list_field(
+                let field = Arc::new(LogicalField::new_list_field(
                     from_substrait_type(inner_type, dfs_names, name_idx)?,
-                    // We ignore Substrait's nullability here to match to_substrait_literal 
+                    // We ignore Substrait's nullability here to match to_substrait_literal
                     // which always creates nullable lists
                     true,
                 ));
                 match list.type_variation_reference {
-                    DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::List(field)),
-                    LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(DataType::LargeList(field)),
+                    DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::List(field)),
+                    LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(LogicalType::LargeList(field)),
                     v => not_impl_err!(
                         "Unsupported Substrait type variation {v} of type {s_kind:?}"
                     )?,
@@ -1456,19 +1461,19 @@ fn from_substrait_type(
                 let value_type = map.value.as_ref().ok_or_else(|| {
                     substrait_datafusion_err!("Map type must have value type")
                 })?;
-                let key_field = Arc::new(Field::new(
+                let key_field = Arc::new(LogicalField::new(
                     "key",
                     from_substrait_type(key_type, dfs_names, name_idx)?,
                     false,
                 ));
-                let value_field = Arc::new(Field::new(
+                let value_field = Arc::new(LogicalField::new(
                     "value",
                     from_substrait_type(value_type, dfs_names, name_idx)?,
                     true,
                 ));
                 match map.type_variation_reference {
                     DEFAULT_CONTAINER_TYPE_VARIATION_REF => {
-                        Ok(DataType::Map(Arc::new(Field::new_struct(
+                        Ok(LogicalType::Map(Arc::new(LogicalField::new_struct(
                             "entries",
                             [key_field, value_field],
                             false, // The inner map field is always non-nullable (Arrow #1697),
@@ -1481,10 +1486,10 @@ fn from_substrait_type(
             }
             r#type::Kind::Decimal(d) => match d.type_variation_reference {
                 DECIMAL_128_TYPE_VARIATION_REF => {
-                    Ok(DataType::Decimal128(d.precision as u8, d.scale as i8))
+                    Ok(LogicalType::Decimal128(d.precision as u8, d.scale as i8))
                 }
                 DECIMAL_256_TYPE_VARIATION_REF => {
-                    Ok(DataType::Decimal256(d.precision as u8, d.scale as i8))
+                    Ok(LogicalType::Decimal256(d.precision as u8, d.scale as i8))
                 }
                 v => not_impl_err!(
                     "Unsupported Substrait type variation {v} of type {s_kind:?}"
@@ -1493,13 +1498,13 @@ fn from_substrait_type(
             r#type::Kind::UserDefined(u) => {
                 match u.type_reference {
                     INTERVAL_YEAR_MONTH_TYPE_REF => {
-                        Ok(DataType::Interval(IntervalUnit::YearMonth))
+                        Ok(LogicalType::Interval(IntervalUnit::YearMonth))
                     }
                     INTERVAL_DAY_TIME_TYPE_REF => {
-                        Ok(DataType::Interval(IntervalUnit::DayTime))
+                        Ok(LogicalType::Interval(IntervalUnit::DayTime))
                     }
                     INTERVAL_MONTH_DAY_NANO_TYPE_REF => {
-                        Ok(DataType::Interval(IntervalUnit::MonthDayNano))
+                        Ok(LogicalType::Interval(IntervalUnit::MonthDayNano))
                     }
                     _ => not_impl_err!(
                         "Unsupported Substrait user defined type with ref {} and variation {}",
@@ -1508,11 +1513,11 @@ fn from_substrait_type(
                     ),
                 }
             },
-            r#type::Kind::Struct(s) => Ok(DataType::Struct(from_substrait_struct_type(
+            r#type::Kind::Struct(s) => Ok(LogicalType::Struct(from_substrait_struct_type(
                 s, dfs_names, name_idx,
             )?)),
-            r#type::Kind::Varchar(_) => Ok(DataType::Utf8),
-            r#type::Kind::FixedChar(_) => Ok(DataType::Utf8),
+            r#type::Kind::Varchar(_) => Ok(LogicalType::Utf8),
+            r#type::Kind::FixedChar(_) => Ok(LogicalType::Utf8),
             _ => not_impl_err!("Unsupported Substrait type: {s_kind:?}"),
         },
         _ => not_impl_err!("`None` Substrait kind is not supported"),
@@ -1523,10 +1528,10 @@ fn from_substrait_struct_type(
     s: &r#type::Struct,
     dfs_names: &[String],
     name_idx: &mut usize,
-) -> Result<Fields> {
+) -> Result<LogicalFields> {
     let mut fields = vec![];
     for (i, f) in s.types.iter().enumerate() {
-        let field = Field::new(
+        let field = LogicalField::new(
             next_struct_field_name(i, dfs_names, name_idx)?,
             from_substrait_type(f, dfs_names, name_idx)?,
             is_substrait_type_nullable(f)?,
@@ -1778,10 +1783,10 @@ fn from_substrait_literal(
             )?;
             match lit.type_variation_reference {
                 DEFAULT_CONTAINER_TYPE_VARIATION_REF => {
-                    ScalarValue::List(ScalarValue::new_list_nullable(&[], &element_type))
+                    ScalarValue::List(ScalarValue::new_list_nullable(&[], &element_type.physical_type()))
                 }
                 LARGE_CONTAINER_TYPE_VARIATION_REF => ScalarValue::LargeList(
-                    ScalarValue::new_large_list(&[], &element_type),
+                    ScalarValue::new_large_list(&[], &element_type.physical_type()),
                 ),
                 others => {
                     return substrait_err!("Unknown type variation reference {others}");
@@ -1958,7 +1963,7 @@ fn from_substrait_null(
                 d.scale as i8,
             )),
             r#type::Kind::List(l) => {
-                let field = Field::new_list_field(
+                let field = LogicalField::new_list_field(
                     from_substrait_type(
                         l.r#type.clone().unwrap().as_ref(),
                         dfs_names,
@@ -1968,10 +1973,10 @@ fn from_substrait_null(
                 );
                 match l.type_variation_reference {
                     DEFAULT_CONTAINER_TYPE_VARIATION_REF => Ok(ScalarValue::List(
-                        Arc::new(GenericListArray::new_null(field.into(), 1)),
+                        Arc::new(GenericListArray::new_null(FieldRef::new(field.into()), 1)),
                     )),
                     LARGE_CONTAINER_TYPE_VARIATION_REF => Ok(ScalarValue::LargeList(
-                        Arc::new(GenericListArray::new_null(field.into(), 1)),
+                        Arc::new(GenericListArray::new_null(FieldRef::new(field.into()), 1)),
                     )),
                     v => not_impl_err!(
                         "Unsupported Substrait type variation {v} of type {kind:?}"
@@ -1979,7 +1984,7 @@ fn from_substrait_null(
                 }
             }
             r#type::Kind::Struct(s) => {
-                let fields = from_substrait_struct_type(s, dfs_names, name_idx)?;
+                let fields: Fields = from_substrait_struct_type(s, dfs_names, name_idx)?.into();
                 Ok(ScalarStructBuilder::new_null(fields))
             }
             _ => not_impl_err!("Unsupported Substrait type for null: {kind:?}"),
diff --git a/datafusion/substrait/src/logical_plan/producer.rs b/datafusion/substrait/src/logical_plan/producer.rs
index 302f38606bfb..07c40f9a9fbd 100644
--- a/datafusion/substrait/src/logical_plan/producer.rs
+++ b/datafusion/substrait/src/logical_plan/producer.rs
@@ -26,14 +26,26 @@ use datafusion::logical_expr::{
     CrossJoin, Distinct, Like, Partitioning, WindowFrameUnits,
 };
 use datafusion::{
-    arrow::datatypes::{DataType, TimeUnit},
+    arrow::datatypes::TimeUnit,
     error::{DataFusionError, Result},
     logical_expr::{WindowFrame, WindowFrameBound},
     prelude::{JoinType, SessionContext},
     scalar::ScalarValue,
 };
 
+use crate::variation_const::{
+    DATE_32_TYPE_VARIATION_REF, DATE_64_TYPE_VARIATION_REF,
+    DECIMAL_128_TYPE_VARIATION_REF, DECIMAL_256_TYPE_VARIATION_REF,
+    DEFAULT_CONTAINER_TYPE_VARIATION_REF, DEFAULT_TYPE_VARIATION_REF,
+    INTERVAL_DAY_TIME_TYPE_REF, INTERVAL_DAY_TIME_TYPE_URL,
+    INTERVAL_MONTH_DAY_NANO_TYPE_REF, INTERVAL_MONTH_DAY_NANO_TYPE_URL,
+    INTERVAL_YEAR_MONTH_TYPE_REF, INTERVAL_YEAR_MONTH_TYPE_URL,
+    LARGE_CONTAINER_TYPE_VARIATION_REF, TIMESTAMP_MICRO_TYPE_VARIATION_REF,
+    TIMESTAMP_MILLI_TYPE_VARIATION_REF, TIMESTAMP_NANO_TYPE_VARIATION_REF,
+    TIMESTAMP_SECOND_TYPE_VARIATION_REF, UNSIGNED_INTEGER_TYPE_VARIATION_REF,
+};
 use datafusion::arrow::array::{Array, GenericListArray, OffsetSizeTrait};
+use datafusion::common::logical_type::LogicalType;
 use datafusion::common::{
     exec_err, internal_err, not_impl_err, plan_err, substrait_datafusion_err,
 };
@@ -91,18 +103,6 @@ use substrait::{
     version,
 };
 
-use crate::variation_const::{
-    DATE_32_TYPE_VARIATION_REF, DATE_64_TYPE_VARIATION_REF,
-    DECIMAL_128_TYPE_VARIATION_REF, DECIMAL_256_TYPE_VARIATION_REF,
-    DEFAULT_CONTAINER_TYPE_VARIATION_REF, DEFAULT_TYPE_VARIATION_REF,
-    INTERVAL_DAY_TIME_TYPE_REF, INTERVAL_DAY_TIME_TYPE_URL,
-    INTERVAL_MONTH_DAY_NANO_TYPE_REF, INTERVAL_MONTH_DAY_NANO_TYPE_URL,
-    INTERVAL_YEAR_MONTH_TYPE_REF, INTERVAL_YEAR_MONTH_TYPE_URL,
-    LARGE_CONTAINER_TYPE_VARIATION_REF, TIMESTAMP_MICRO_TYPE_VARIATION_REF,
-    TIMESTAMP_MILLI_TYPE_VARIATION_REF, TIMESTAMP_NANO_TYPE_VARIATION_REF,
-    TIMESTAMP_SECOND_TYPE_VARIATION_REF, UNSIGNED_INTEGER_TYPE_VARIATION_REF,
-};
-
 /// Convert DataFusion LogicalPlan to Substrait Plan
 pub fn to_substrait_plan(plan: &LogicalPlan, ctx: &SessionContext) -> Result<Box<Plan>> {
     // Parse relation nodes
@@ -586,9 +586,9 @@ fn to_substrait_named_struct(schema: &DFSchemaRef) -> Result<NamedStruct> {
     // Substrait wants a list of all field names, including nested fields from structs,
     // also from within e.g. lists and maps. However, it does not want the list and map field names
     // themselves - only proper structs fields are considered to have useful names.
-    fn names_dfs(dtype: &DataType) -> Result<Vec<String>> {
+    fn names_dfs(dtype: &LogicalType) -> Result<Vec<String>> {
         match dtype {
-            DataType::Struct(fields) => {
+            LogicalType::Struct(fields) => {
                 let mut names = Vec::new();
                 for field in fields {
                     names.push(field.name().to_string());
@@ -596,10 +596,10 @@ fn to_substrait_named_struct(schema: &DFSchemaRef) -> Result<NamedStruct> {
                 }
                 Ok(names)
             }
-            DataType::List(l) => names_dfs(l.data_type()),
-            DataType::LargeList(l) => names_dfs(l.data_type()),
-            DataType::Map(m, _) => match m.data_type() {
-                DataType::Struct(key_and_value) if key_and_value.len() == 2 => {
+            LogicalType::List(l) => names_dfs(l.data_type()),
+            LogicalType::LargeList(l) => names_dfs(l.data_type()),
+            LogicalType::Map(m, _) => match m.data_type() {
+                LogicalType::Struct(key_and_value) if key_and_value.len() == 2 => {
                     let key_names =
                         names_dfs(key_and_value.first().unwrap().data_type())?;
                     let value_names =
@@ -1433,83 +1433,83 @@ pub fn to_substrait_rex(
     }
 }
 
-fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::Type> {
+fn to_substrait_type(dt: &LogicalType, nullable: bool) -> Result<substrait::proto::Type> {
     let nullability = if nullable {
         r#type::Nullability::Nullable as i32
     } else {
         r#type::Nullability::Required as i32
     };
     match dt {
-        DataType::Null => internal_err!("Null cast is not valid"),
-        DataType::Boolean => Ok(substrait::proto::Type {
+        LogicalType::Null => internal_err!("Null cast is not valid"),
+        LogicalType::Boolean => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Bool(r#type::Boolean {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Int8 => Ok(substrait::proto::Type {
+        LogicalType::Int8 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I8(r#type::I8 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::UInt8 => Ok(substrait::proto::Type {
+        LogicalType::UInt8 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I8(r#type::I8 {
                 type_variation_reference: UNSIGNED_INTEGER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Int16 => Ok(substrait::proto::Type {
+        LogicalType::Int16 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I16(r#type::I16 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::UInt16 => Ok(substrait::proto::Type {
+        LogicalType::UInt16 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I16(r#type::I16 {
                 type_variation_reference: UNSIGNED_INTEGER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Int32 => Ok(substrait::proto::Type {
+        LogicalType::Int32 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I32(r#type::I32 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::UInt32 => Ok(substrait::proto::Type {
+        LogicalType::UInt32 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I32(r#type::I32 {
                 type_variation_reference: UNSIGNED_INTEGER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Int64 => Ok(substrait::proto::Type {
+        LogicalType::Int64 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I64(r#type::I64 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::UInt64 => Ok(substrait::proto::Type {
+        LogicalType::UInt64 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::I64(r#type::I64 {
                 type_variation_reference: UNSIGNED_INTEGER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
         // Float16 is not supported in Substrait
-        DataType::Float32 => Ok(substrait::proto::Type {
+        LogicalType::Float32 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Fp32(r#type::Fp32 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Float64 => Ok(substrait::proto::Type {
+        LogicalType::Float64 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Fp64(r#type::Fp64 {
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
         // Timezone is ignored.
-        DataType::Timestamp(unit, _) => {
+        LogicalType::Timestamp(unit, _) => {
             let type_variation_reference = match unit {
                 TimeUnit::Second => TIMESTAMP_SECOND_TYPE_VARIATION_REF,
                 TimeUnit::Millisecond => TIMESTAMP_MILLI_TYPE_VARIATION_REF,
@@ -1523,19 +1523,19 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 })),
             })
         }
-        DataType::Date32 => Ok(substrait::proto::Type {
+        LogicalType::Date32 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Date(r#type::Date {
                 type_variation_reference: DATE_32_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Date64 => Ok(substrait::proto::Type {
+        LogicalType::Date64 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Date(r#type::Date {
                 type_variation_reference: DATE_64_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Interval(interval_unit) => {
+        LogicalType::Interval(interval_unit) => {
             // define two type parameters for convenience
             let i32_param = Parameter {
                 parameter: Some(parameter::Parameter::DataType(substrait::proto::Type {
@@ -1578,38 +1578,38 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 })),
             })
         }
-        DataType::Binary => Ok(substrait::proto::Type {
+        LogicalType::Binary => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Binary(r#type::Binary {
                 type_variation_reference: DEFAULT_CONTAINER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::FixedSizeBinary(length) => Ok(substrait::proto::Type {
+        LogicalType::FixedSizeBinary(length) => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::FixedBinary(r#type::FixedBinary {
                 length: *length,
                 type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::LargeBinary => Ok(substrait::proto::Type {
+        LogicalType::LargeBinary => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Binary(r#type::Binary {
                 type_variation_reference: LARGE_CONTAINER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::Utf8 => Ok(substrait::proto::Type {
+        LogicalType::Utf8 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::String(r#type::String {
                 type_variation_reference: DEFAULT_CONTAINER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::LargeUtf8 => Ok(substrait::proto::Type {
+        LogicalType::LargeUtf8 => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::String(r#type::String {
                 type_variation_reference: LARGE_CONTAINER_TYPE_VARIATION_REF,
                 nullability,
             })),
         }),
-        DataType::List(inner) => {
+        LogicalType::List(inner) => {
             let inner_type = to_substrait_type(inner.data_type(), inner.is_nullable())?;
             Ok(substrait::proto::Type {
                 kind: Some(r#type::Kind::List(Box::new(r#type::List {
@@ -1619,7 +1619,7 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 }))),
             })
         }
-        DataType::LargeList(inner) => {
+        LogicalType::LargeList(inner) => {
             let inner_type = to_substrait_type(inner.data_type(), inner.is_nullable())?;
             Ok(substrait::proto::Type {
                 kind: Some(r#type::Kind::List(Box::new(r#type::List {
@@ -1629,8 +1629,8 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 }))),
             })
         }
-        DataType::Map(inner, _) => match inner.data_type() {
-            DataType::Struct(key_and_value) if key_and_value.len() == 2 => {
+        LogicalType::Map(inner, _) => match inner.data_type() {
+            LogicalType::Struct(key_and_value) if key_and_value.len() == 2 => {
                 let key_type = to_substrait_type(
                     key_and_value[0].data_type(),
                     key_and_value[0].is_nullable(),
@@ -1650,7 +1650,7 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
             }
             _ => plan_err!("Map fields must contain a Struct with exactly 2 fields"),
         },
-        DataType::Struct(fields) => {
+        LogicalType::Struct(fields) => {
             let field_types = fields
                 .iter()
                 .map(|field| to_substrait_type(field.data_type(), field.is_nullable()))
@@ -1663,7 +1663,7 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 })),
             })
         }
-        DataType::Decimal128(p, s) => Ok(substrait::proto::Type {
+        LogicalType::Decimal128(p, s) => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Decimal(r#type::Decimal {
                 type_variation_reference: DECIMAL_128_TYPE_VARIATION_REF,
                 nullability,
@@ -1671,7 +1671,7 @@ fn to_substrait_type(dt: &DataType, nullable: bool) -> Result<substrait::proto::
                 precision: *p as i32,
             })),
         }),
-        DataType::Decimal256(p, s) => Ok(substrait::proto::Type {
+        LogicalType::Decimal256(p, s) => Ok(substrait::proto::Type {
             kind: Some(r#type::Kind::Decimal(r#type::Decimal {
                 type_variation_reference: DECIMAL_256_TYPE_VARIATION_REF,
                 nullability,
@@ -1897,7 +1897,7 @@ fn to_substrait_literal(value: &ScalarValue) -> Result<Literal> {
             nullable: true,
             type_variation_reference: DEFAULT_TYPE_VARIATION_REF,
             literal_type: Some(LiteralType::Null(to_substrait_type(
-                &value.data_type(),
+                &value.data_type().into(),
                 true,
             )?)),
         });
@@ -2097,7 +2097,7 @@ fn convert_array_to_literal_list<T: OffsetSizeTrait>(
         .collect::<Result<Vec<_>>>()?;
 
     if values.is_empty() {
-        let et = match to_substrait_type(array.data_type(), array.is_nullable())? {
+        let et = match to_substrait_type(&array.data_type().to_owned().into(), array.is_nullable())? {
             substrait::proto::Type {
                 kind: Some(r#type::Kind::List(lt)),
             } => lt.as_ref().to_owned(),
@@ -2223,7 +2223,7 @@ mod test {
         from_substrait_literal_without_names, from_substrait_type_without_names,
     };
     use datafusion::arrow::array::GenericListArray;
-    use datafusion::arrow::datatypes::Field;
+    use datafusion::arrow::datatypes::{DataType, Field};
     use datafusion::common::scalar::ScalarStructBuilder;
 
     use super::*;
@@ -2376,9 +2376,10 @@ mod test {
 
         // As DataFusion doesn't consider nullability as a property of the type, but field,
         // it doesn't matter if we set nullability to true or false here.
-        let substrait = to_substrait_type(&dt, true)?;
+        let lt = dt.into();
+        let substrait = to_substrait_type(&lt, true)?;
         let roundtrip_dt = from_substrait_type_without_names(&substrait)?;
-        assert_eq!(dt, roundtrip_dt);
+        assert_eq!(lt, roundtrip_dt);
         Ok(())
     }
 }