diff --git a/README.md b/README.md
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+++ b/README.md
@@ -35,6 +35,7 @@ This library is work in progress so the API may change before the official relea
   - [Dataframe](doc/dataframe.md)
   - [Streaming](doc/streaming.md)
   - [Cluster](doc/cluster.md)
+  - [Java](doc/java.md)
   - [Python](doc/python.md)
   - [Configuration](doc/configuration.md)
 
diff --git a/doc/java.md b/doc/java.md
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@@ -0,0 +1,115 @@
+# Using the library in Java
+
+The library is written in Scala and the API is primarily intended to be used with Scala. But you can also use the library in 
+Java because of the Scala/Java interoperability. 
+
+
+## RDD
+
+Please, refer to the detailed documentation of [RDD support](rdd.md) for the full list of available features.
+The RDD functions are available in `RedisContext`. Example:
+
+```java
+SparkConf sparkConf = new SparkConf()
+                            .setAppName("MyApp")
+                            .setMaster("local[*]")
+                            .set("spark.redis.host", "localhost")
+                            .set("spark.redis.port", "6379");
+
+RedisConfig redisConfig = RedisConfig.fromSparkConf(sparkConf);
+ReadWriteConfig readWriteConfig = ReadWriteConfig.fromSparkConf(sparkConf);
+
+JavaSparkContext jsc = new JavaSparkContext(sparkConf);
+RedisContext redisContext = new RedisContext(jsc.sc());
+
+JavaRDD<Tuple2<String, String>> rdd = jsc.parallelize(Arrays.asList(Tuple2.apply("myKey", "Hello")));
+int ttl = 0;
+
+redisContext.toRedisKV(rdd.rdd(), ttl, redisConfig, readWriteConfig);
+
+``` 
+
+## Datasets and DataFrames
+
+The Dataset/DataFrame API is the same in Java and Scala. Please, refer to [DataFrame page](dataframe.md) for details. Here is an
+example with Java:
+
+```Java
+public class Person {
+
+    private String name;
+    private Integer age;
+
+    public Person() {
+    }
+
+    public Person(String name, Integer age) {
+        this.name = name;
+        this.age = age;
+    }
+
+    public String getName() {
+        return name;
+    }
+    
+    public void setName(String name) {
+        this.name = name;
+    }
+    
+    public Integer getAge() {
+        return age;
+    }
+    
+    public void setAge(Integer age) {
+        this.age = age;
+    }
+}
+
+```
+
+```Java
+SparkSession spark = SparkSession
+                .builder()
+                .appName("MyApp")
+                .master("local[*]")
+                .config("spark.redis.host", "localhost")
+                .config("spark.redis.port", "6379")
+                .getOrCreate();
+
+Dataset<Row> df = spark.createDataFrame(Arrays.asList(
+                new Person("John", 35),
+                new Person("Peter", 40)), Person.class);
+
+df.write()
+        .format("org.apache.spark.sql.redis")
+        .option("table", "person")
+        .option("key.column", "name")
+        .mode(SaveMode.Overwrite)
+        .save();
+```
+
+## Streaming
+
+The following example demonstrates how to create a stream from Redis list `myList`. Please, refer to [Streaming](streaming.md) for more details.
+
+```java
+SparkConf sparkConf = new SparkConf()
+            .setAppName("MyApp")
+            .setMaster("local[*]")
+            .set("redis.host", "localhost")
+            .set("redis.port", "6379");
+
+JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
+
+RedisConfig redisConfig = new RedisConfig(new RedisEndpoint(sparkConf));
+
+RedisStreamingContext redisStreamingContext = new RedisStreamingContext(jssc.ssc());
+String[] keys = new String[]{"myList"};
+RedisInputDStream<Tuple2<String, String>> redisStream =
+        redisStreamingContext.createRedisStream(keys, StorageLevel.MEMORY_ONLY(), redisConfig);
+
+redisStream.print();
+
+jssc.start();
+jssc.awaitTermination();
+```
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