diff --git a/numcodecs/__init__.py b/numcodecs/__init__.py
index 425d10df..973d6ea1 100644
--- a/numcodecs/__init__.py
+++ b/numcodecs/__init__.py
@@ -49,6 +49,9 @@
 except ImportError:  # pragma: no cover
     pass
 
+from numcodecs.astype import AsType
+register_codec(AsType)
+
 from numcodecs.delta import Delta
 register_codec(Delta)
 
diff --git a/numcodecs/astype.py b/numcodecs/astype.py
new file mode 100644
index 00000000..6ecc658e
--- /dev/null
+++ b/numcodecs/astype.py
@@ -0,0 +1,88 @@
+# -*- coding: utf-8 -*-
+from __future__ import absolute_import, print_function, division
+
+import numpy as np
+
+from numcodecs.abc import Codec
+from numcodecs.compat import buffer_copy, ndarray_from_buffer
+
+
+
+class AsType(Codec):
+    """Filter to convert data between different types.
+
+    Parameters
+    ----------
+    encode_dtype : dtype
+        Data type to use for encoded data.
+    decode_dtype : dtype, optional
+        Data type to use for decoded data.
+
+    Notes
+    -----
+    If `encode_dtype` is of lower precision than `decode_dtype`, please be
+    aware that data loss can occur by writing data to disk using this filter.
+    No checks are made to ensure the casting will work in that direction and
+    data corruption will occur.
+
+    Examples
+    --------
+    >>> import numcodecs
+    >>> import numpy as np
+    >>> x = np.arange(100, 120, 2, dtype=np.int8)
+    >>> x
+    array([100, 102, 104, 106, 108, 110, 112, 114, 116, 118], dtype=int8)
+    >>> f = numcodecs.AsType(encode_dtype=x.dtype, decode_dtype=np.int64)
+    >>> y = f.decode(x)
+    >>> y
+    array([100, 102, 104, 106, 108, 110, 112, 114, 116, 118])
+    >>> z = f.encode(y)
+    >>> z
+    array([100, 102, 104, 106, 108, 110, 112, 114, 116, 118], dtype=int8)
+
+    """  # flake8: noqa
+
+    codec_id = 'astype'
+
+    def __init__(self, encode_dtype, decode_dtype):
+        self.encode_dtype = np.dtype(encode_dtype)
+        self.decode_dtype = np.dtype(decode_dtype)
+
+    def encode(self, buf):
+
+        # view input data as 1D array
+        arr = ndarray_from_buffer(buf, self.decode_dtype)
+
+        # convert and copy
+        enc = arr.astype(self.encode_dtype)
+
+        return enc
+
+    def decode(self, buf, out=None):
+
+        # view encoded data as 1D array
+        enc = ndarray_from_buffer(buf, self.encode_dtype)
+
+        # convert and copy
+        dec = enc.astype(self.decode_dtype)
+
+        # handle output
+        out = buffer_copy(dec, out)
+
+        return out
+
+    def get_config(self):
+        config = dict()
+        config['id'] = self.codec_id
+        config['encode_dtype'] = self.encode_dtype.str
+        config['decode_dtype'] = self.decode_dtype.str
+        return config
+
+    def __repr__(self):
+        return (
+            '%s(encode_dtype=%r, decode_dtype=%r)' % (
+                type(self).__name__,
+                self.encode_dtype.str,
+                self.decode_dtype.str
+            )
+        )
diff --git a/numcodecs/tests/test_astype.py b/numcodecs/tests/test_astype.py
new file mode 100644
index 00000000..9211b164
--- /dev/null
+++ b/numcodecs/tests/test_astype.py
@@ -0,0 +1,60 @@
+# -*- coding: utf-8 -*-
+from __future__ import absolute_import, print_function, division
+
+
+import numpy as np
+from numpy.testing import assert_array_equal
+from nose.tools import eq_ as eq
+
+
+from numcodecs.astype import AsType
+from numcodecs.tests.common import check_encode_decode, check_config, \
+    check_repr
+
+
+# mix of dtypes: integer, float
+# mix of shapes: 1D, 2D, 3D
+# mix of orders: C, F
+arrays = [
+    np.arange(1000, dtype='i4'),
+    np.linspace(1000, 1001, 1000, dtype='f8').reshape(100, 10),
+    np.random.normal(loc=1000, scale=1, size=(10, 10, 10)),
+    np.random.randint(0, 200, size=1000, dtype='u2').reshape(100, 10,
+                                                             order='F'),
+]
+
+
+def test_encode_decode():
+    for arr in arrays:
+        codec = AsType(encode_dtype=arr.dtype, decode_dtype=arr.dtype)
+        check_encode_decode(arr, codec)
+
+
+def test_decode():
+    encode_dtype, decode_dtype = '<i4', '<i8'
+    codec = AsType(encode_dtype=encode_dtype, decode_dtype=decode_dtype)
+    arr = np.arange(10, 20, 1, dtype=encode_dtype)
+    expect = arr.astype(decode_dtype)
+    actual = codec.decode(arr)
+    assert_array_equal(expect, actual)
+    eq(np.dtype(decode_dtype), actual.dtype)
+
+
+def test_encode():
+    encode_dtype, decode_dtype = '<i4', '<i8'
+    codec = AsType(encode_dtype=encode_dtype, decode_dtype=decode_dtype)
+    arr = np.arange(10, 20, 1, dtype=decode_dtype)
+    expect = arr.astype(encode_dtype)
+    actual = codec.encode(arr)
+    assert_array_equal(expect, actual)
+    eq(np.dtype(encode_dtype), actual.dtype)
+
+
+def test_config():
+    encode_dtype, decode_dtype = '<i4', '<i8'
+    codec = AsType(encode_dtype=encode_dtype, decode_dtype=decode_dtype)
+    check_config(codec)
+
+
+def test_repr():
+    check_repr("AsType(encode_dtype='<i4', decode_dtype='<i2')")