diff --git a/pyspark_datasources/fake.py b/pyspark_datasources/fake.py
index fd83900..2b9447c 100644
--- a/pyspark_datasources/fake.py
+++ b/pyspark_datasources/fake.py
@@ -1,5 +1,35 @@
-from pyspark.sql.datasource import DataSource, DataSourceReader
-from pyspark.sql.types import StructType, StringType
+from typing import List
+
+from pyspark.sql.datasource import (
+    DataSource,
+    DataSourceReader,
+    DataSourceStreamReader,
+    InputPartition,
+)
+from pyspark.sql.types import StringType, StructType
+
+
+def _validate_faker_schema(schema):
+    # Verify the library is installed correctly.
+    try:
+        from faker import Faker
+    except ImportError:
+        raise Exception("You need to install `faker` to use the fake datasource.")
+
+    fake = Faker()
+    for field in schema.fields:
+        try:
+            getattr(fake, field.name)()
+        except AttributeError:
+            raise Exception(
+                f"Unable to find a method called `{field.name}` in faker. "
+                f"Please check Faker's documentation to see supported methods."
+            )
+        if field.dataType != StringType():
+            raise Exception(
+                f"Field `{field.name}` is not a StringType. "
+                f"Only StringType is supported in the fake datasource."
+            )
 
 
 class FakeDataSource(DataSource):
@@ -19,6 +49,7 @@ class FakeDataSource(DataSource):
     - The fake data source relies on the `faker` library. Make sure it is installed and accessible.
     - Only string type fields are supported, and each field name must correspond to a method name in
       the `faker` library.
+    - When using the stream reader, `numRows` is the number of rows per microbatch.
 
     Examples
     --------
@@ -61,6 +92,21 @@ class FakeDataSource(DataSource):
     |  Caitlin Reed|1983-06-22|  89813|Pennsylvania|
     | Douglas James|2007-01-18|  46226|     Alabama|
     +--------------+----------+-------+------------+
+
+    Streaming fake data:
+
+    >>> stream = spark.readStream.format("fake").load().writeStream.format("console").start()
+    Batch: 0
+    +--------------+----------+-------+------------+
+    |          name|      date|zipcode|       state|
+    +--------------+----------+-------+------------+
+    |    Tommy Diaz|1976-11-17|  27627|South Dakota|
+    |Jonathan Perez|1986-02-23|  81307|Rhode Island|
+    |  Julia Farmer|1990-10-10|  40482|    Virginia|
+    +--------------+----------+-------+------------+
+    Batch: 1
+    ...
+    >>> stream.stop()
     """
 
     @classmethod
@@ -70,40 +116,24 @@ def name(cls):
     def schema(self):
         return "name string, date string, zipcode string, state string"
 
-    def reader(self, schema: StructType):
-        # Verify the library is installed correctly.
-        try:
-            from faker import Faker
-        except ImportError:
-            raise Exception("You need to install `faker` to use the fake datasource.")
-
-        # Check the schema is valid before proceed to reading.
-        fake = Faker()
-        for field in schema.fields:
-            try:
-                getattr(fake, field.name)()
-            except AttributeError:
-                raise Exception(
-                    f"Unable to find a method called `{field.name}` in faker. "
-                    f"Please check Faker's documentation to see supported methods."
-                )
-            if field.dataType != StringType():
-                raise Exception(
-                    f"Field `{field.name}` is not a StringType. "
-                    f"Only StringType is supported in the fake datasource."
-                )
-
+    def reader(self, schema: StructType) -> "FakeDataSourceReader":
+        _validate_faker_schema(schema)
         return FakeDataSourceReader(schema, self.options)
 
+    def streamReader(self, schema) -> "FakeDataSourceStreamReader":
+        _validate_faker_schema(schema)
+        return FakeDataSourceStreamReader(schema, self.options)
+
 
 class FakeDataSourceReader(DataSourceReader):
 
-    def __init__(self, schema, options):
+    def __init__(self, schema, options) -> None:
         self.schema: StructType = schema
         self.options = options
 
     def read(self, partition):
         from faker import Faker
+
         fake = Faker()
         # Note: every value in this `self.options` dictionary is a string.
         num_rows = int(self.options.get("numRows", 3))
@@ -113,3 +143,32 @@ def read(self, partition):
                 value = getattr(fake, field.name)()
                 row.append(value)
             yield tuple(row)
+
+
+class FakeDataSourceStreamReader(DataSourceStreamReader):
+    def __init__(self, schema, options) -> None:
+        self.schema: StructType = schema
+        self.rows_per_microbatch = int(options.get("numRows", 3))
+        self.options = options
+        self.offset = 0
+
+    def initialOffset(self) -> dict:
+        return {"offset": 0}
+
+    def latestOffset(self) -> dict:
+        self.offset += self.rows_per_microbatch
+        return {"offset": self.offset}
+
+    def partitions(self, start, end) -> List[InputPartition]:
+        return [InputPartition(end["offset"] - start["offset"])]
+
+    def read(self, partition):
+        from faker import Faker
+
+        fake = Faker()
+        for _ in range(partition.value):
+            row = []
+            for field in self.schema.fields:
+                value = getattr(fake, field.name)()
+                row.append(value)
+            yield tuple(row)
diff --git a/tests/test_data_sources.py b/tests/test_data_sources.py
index 9ca74c1..1d337e2 100644
--- a/tests/test_data_sources.py
+++ b/tests/test_data_sources.py
@@ -17,6 +17,21 @@ def test_github_datasource(spark):
     assert len(prs) > 0
 
 
+def test_fake_datasource_stream(spark):
+    spark.dataSource.register(FakeDataSource)
+    (
+        spark.readStream.format("fake")
+        .load()
+        .writeStream.format("memory")
+        .queryName("result")
+        .trigger(once=True)
+        .start()
+        .awaitTermination()
+    )
+    spark.sql("SELECT * FROM result").show()
+    assert spark.sql("SELECT * FROM result").count() == 3
+
+
 def test_fake_datasource(spark):
     spark.dataSource.register(FakeDataSource)
     df = spark.read.format("fake").load()