diff --git a/sdk/python/feast/feature_store.py b/sdk/python/feast/feature_store.py
index 2af349cd3e..50213e80dc 100644
--- a/sdk/python/feast/feature_store.py
+++ b/sdk/python/feast/feature_store.py
@@ -809,6 +809,26 @@ def tqdm_builder(length):
                 feature_view, self.project, start_date, end_date
             )
 
+    @log_exceptions_and_usage
+    def write_to_online_store(
+        self, feature_view_name: str, df: pd.DataFrame,
+    ):
+        """
+        ingests data directly into the Online store
+        """
+        if not flags_helper.enable_direct_ingestion_to_online_store(self.config):
+            raise ExperimentalFeatureNotEnabled(
+                flags.FLAG_DIRECT_INGEST_TO_ONLINE_STORE
+            )
+
+        # TODO: restrict this to work with online StreamFeatureViews and validate the FeatureView type
+        feature_view = self._registry.get_feature_view(feature_view_name, self.project)
+        entities = []
+        for entity_name in feature_view.entities:
+            entities.append(self._registry.get_entity(entity_name, self.project))
+        provider = self._get_provider()
+        provider.ingest_df(feature_view, entities, df)
+
     @log_exceptions_and_usage
     def get_online_features(
         self,
diff --git a/sdk/python/feast/flags.py b/sdk/python/feast/flags.py
index c9e7416863..5c6357ec26 100644
--- a/sdk/python/feast/flags.py
+++ b/sdk/python/feast/flags.py
@@ -2,6 +2,7 @@
 FLAG_ON_DEMAND_TRANSFORM_NAME = "on_demand_transforms"
 FLAG_PYTHON_FEATURE_SERVER_NAME = "python_feature_server"
 FLAG_AWS_LAMBDA_FEATURE_SERVER_NAME = "aws_lambda_feature_server"
+FLAG_DIRECT_INGEST_TO_ONLINE_STORE = "direct_ingest_to_online_store"
 ENV_FLAG_IS_TEST = "IS_TEST"
 
 FLAG_NAMES = {
@@ -9,4 +10,5 @@
     FLAG_ON_DEMAND_TRANSFORM_NAME,
     FLAG_PYTHON_FEATURE_SERVER_NAME,
     FLAG_AWS_LAMBDA_FEATURE_SERVER_NAME,
+    FLAG_DIRECT_INGEST_TO_ONLINE_STORE,
 }
diff --git a/sdk/python/feast/flags_helper.py b/sdk/python/feast/flags_helper.py
index 85770c39ec..89784d6ecc 100644
--- a/sdk/python/feast/flags_helper.py
+++ b/sdk/python/feast/flags_helper.py
@@ -41,3 +41,7 @@ def enable_python_feature_server(repo_config: RepoConfig) -> bool:
 
 def enable_aws_lambda_feature_server(repo_config: RepoConfig) -> bool:
     return feature_flag_enabled(repo_config, flags.FLAG_AWS_LAMBDA_FEATURE_SERVER_NAME)
+
+
+def enable_direct_ingestion_to_online_store(repo_config: RepoConfig) -> bool:
+    return feature_flag_enabled(repo_config, flags.FLAG_DIRECT_INGEST_TO_ONLINE_STORE)
diff --git a/sdk/python/feast/infra/passthrough_provider.py b/sdk/python/feast/infra/passthrough_provider.py
index 3e4c0a3485..45745cfed0 100644
--- a/sdk/python/feast/infra/passthrough_provider.py
+++ b/sdk/python/feast/infra/passthrough_provider.py
@@ -2,6 +2,7 @@
 from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
 
 import pandas
+import pyarrow as pa
 from tqdm import tqdm
 
 from feast.entity import Entity
@@ -82,6 +83,21 @@ def online_read(
 
         return result
 
+    def ingest_df(
+        self, feature_view: FeatureView, entities: List[Entity], df: pandas.DataFrame,
+    ):
+        table = pa.Table.from_pandas(df)
+
+        if feature_view.batch_source.field_mapping is not None:
+            table = _run_field_mapping(table, feature_view.batch_source.field_mapping)
+
+        join_keys = [entity.join_key for entity in entities]
+        rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
+
+        self.online_write_batch(
+            self.repo_config, feature_view, rows_to_write, progress=None
+        )
+
     def materialize_single_feature_view(
         self,
         config: RepoConfig,
diff --git a/sdk/python/feast/infra/provider.py b/sdk/python/feast/infra/provider.py
index 4debd59aa8..4b7c8069f2 100644
--- a/sdk/python/feast/infra/provider.py
+++ b/sdk/python/feast/infra/provider.py
@@ -98,6 +98,14 @@ def online_write_batch(
         """
         ...
 
+    def ingest_df(
+        self, feature_view: FeatureView, entities: List[Entity], df: pandas.DataFrame,
+    ):
+        """
+        Ingests a DataFrame directly into the online store
+        """
+        pass
+
     @abc.abstractmethod
     def materialize_single_feature_view(
         self,
diff --git a/sdk/python/tests/integration/online_store/test_universal_online.py b/sdk/python/tests/integration/online_store/test_universal_online.py
index b9824ae163..259df20c57 100644
--- a/sdk/python/tests/integration/online_store/test_universal_online.py
+++ b/sdk/python/tests/integration/online_store/test_universal_online.py
@@ -1,3 +1,4 @@
+import datetime
 import itertools
 import unittest
 from datetime import timedelta
@@ -19,6 +20,49 @@
     driver,
     location,
 )
+from tests.integration.feature_repos.universal.feature_views import (
+    create_driver_hourly_stats_feature_view,
+)
+
+
+@pytest.mark.integration
+def test_write_to_online_store(environment, universal_data_sources):
+    fs = environment.feature_store
+    entities, datasets, data_sources = universal_data_sources
+    driver_hourly_stats = create_driver_hourly_stats_feature_view(
+        data_sources["driver"]
+    )
+    driver_entity = driver()
+
+    # Register Feature View and Entity
+    fs.apply([driver_hourly_stats, driver_entity])
+
+    # fake data to ingest into Online Store
+    data = {
+        "driver_id": [123],
+        "conv_rate": [0.85],
+        "acc_rate": [0.91],
+        "avg_daily_trips": [14],
+        "event_timestamp": [pd.Timestamp(datetime.datetime.utcnow()).round("ms")],
+        "created": [pd.Timestamp(datetime.datetime.utcnow()).round("ms")],
+    }
+    df_data = pd.DataFrame(data)
+
+    # directly ingest data into the Online Store
+    fs.write_to_online_store("driver_stats", df_data)
+
+    # assert the right data is in the Online Store
+    df = fs.get_online_features(
+        features=[
+            "driver_stats:avg_daily_trips",
+            "driver_stats:acc_rate",
+            "driver_stats:conv_rate",
+        ],
+        entity_rows=[{"driver": 123}],
+    ).to_df()
+    assert df["avg_daily_trips"].iloc[0] == 14
+    assert df["acc_rate"].iloc[0] == 0.91
+    assert df["conv_rate"].iloc[0] == 0.85
 
 
 @pytest.mark.integration