diff --git a/sdk/python/feast/feature_store.py b/sdk/python/feast/feature_store.py
index bfb8a59b2bb..83aaafd6863 100644
--- a/sdk/python/feast/feature_store.py
+++ b/sdk/python/feast/feature_store.py
@@ -2037,11 +2037,10 @@ def _augment_response_with_on_demand_transforms(
 
             proto_values = []
             for selected_feature in selected_subset:
-                if odfv.mode in ["python", "pandas"]:
-                    feature_vector = transformed_features[selected_feature]
-                    proto_values.append(
-                        python_values_to_proto_values(feature_vector, ValueType.UNKNOWN)
-                    )
+                feature_vector = transformed_features[selected_feature]
+                proto_values.append(
+                    python_values_to_proto_values(feature_vector, ValueType.UNKNOWN)
+                )
 
             odfv_result_names |= set(selected_subset)
 
diff --git a/sdk/python/feast/infra/offline_stores/offline_store.py b/sdk/python/feast/infra/offline_stores/offline_store.py
index aaed78dd459..6c16ef26439 100644
--- a/sdk/python/feast/infra/offline_stores/offline_store.py
+++ b/sdk/python/feast/infra/offline_stores/offline_store.py
@@ -128,7 +128,7 @@ def to_arrow(
         features_df = self._to_df_internal(timeout=timeout)
         if self.on_demand_feature_views:
             for odfv in self.on_demand_feature_views:
-                if odfv.mode != "pandas":
+                if odfv.mode not in {"pandas", "substrait"}:
                     raise Exception(
                         f'OnDemandFeatureView mode "{odfv.mode}" not supported for offline processing.'
                     )
diff --git a/sdk/python/feast/on_demand_feature_view.py b/sdk/python/feast/on_demand_feature_view.py
index 8d51edbe587..f83500cbc9b 100644
--- a/sdk/python/feast/on_demand_feature_view.py
+++ b/sdk/python/feast/on_demand_feature_view.py
@@ -465,7 +465,9 @@ def get_transformed_features(
             return self.get_transformed_features_dict(
                 feature_dict=features,
             )
-        elif self.mode == "pandas" and isinstance(features, pd.DataFrame):
+        elif self.mode in {"pandas", "substrait"} and isinstance(
+            features, pd.DataFrame
+        ):
             return self.get_transformed_features_df(
                 df_with_features=features,
                 full_feature_names=full_feature_names,
diff --git a/sdk/python/tests/unit/test_on_demand_substrait_transformation.py b/sdk/python/tests/unit/test_substrait_transformation.py
similarity index 73%
rename from sdk/python/tests/unit/test_on_demand_substrait_transformation.py
rename to sdk/python/tests/unit/test_substrait_transformation.py
index 378aa7ce3bd..28ab68c70be 100644
--- a/sdk/python/tests/unit/test_on_demand_substrait_transformation.py
+++ b/sdk/python/tests/unit/test_substrait_transformation.py
@@ -60,6 +60,7 @@ def test_ibis_pandas_parity():
         @on_demand_feature_view(
             sources=[driver_stats_fv],
             schema=[Field(name="conv_rate_plus_acc", dtype=Float64)],
+            mode="pandas",
         )
         def pandas_view(inputs: pd.DataFrame) -> pd.DataFrame:
             df = pd.DataFrame()
@@ -84,30 +85,50 @@ def substrait_view(inputs: Table) -> Table:
             [driver, driver_stats_source, driver_stats_fv, substrait_view, pandas_view]
         )
 
+        store.materialize(
+            start_date=start_date,
+            end_date=end_date,
+        )
+
         entity_df = pd.DataFrame.from_dict(
             {
                 # entity's join key -> entity values
                 "driver_id": [1001, 1002, 1003],
                 # "event_timestamp" (reserved key) -> timestamps
                 "event_timestamp": [
-                    datetime(2021, 4, 12, 10, 59, 42),
-                    datetime(2021, 4, 12, 8, 12, 10),
-                    datetime(2021, 4, 12, 16, 40, 26),
+                    start_date + timedelta(days=4),
+                    start_date + timedelta(days=5),
+                    start_date + timedelta(days=6),
                 ],
             }
         )
 
+        requested_features = [
+            "driver_hourly_stats:conv_rate",
+            "driver_hourly_stats:acc_rate",
+            "driver_hourly_stats:avg_daily_trips",
+            "substrait_view:conv_rate_plus_acc_substrait",
+            "pandas_view:conv_rate_plus_acc",
+        ]
+
         training_df = store.get_historical_features(
-            entity_df=entity_df,
-            features=[
-                "driver_hourly_stats:conv_rate",
-                "driver_hourly_stats:acc_rate",
-                "driver_hourly_stats:avg_daily_trips",
-                "substrait_view:conv_rate_plus_acc_substrait",
-                "pandas_view:conv_rate_plus_acc",
-            ],
-        ).to_df()
+            entity_df=entity_df, features=requested_features
+        )
+
+        assert training_df.to_df()["conv_rate_plus_acc"].equals(
+            training_df.to_df()["conv_rate_plus_acc_substrait"]
+        )
+
+        assert training_df.to_arrow()["conv_rate_plus_acc"].equals(
+            training_df.to_arrow()["conv_rate_plus_acc_substrait"]
+        )
+
+        online_response = store.get_online_features(
+            features=requested_features,
+            entity_rows=[{"driver_id": 1001}, {"driver_id": 1002}, {"driver_id": 1003}],
+        )
 
-        assert training_df["conv_rate_plus_acc"].equals(
-            training_df["conv_rate_plus_acc_substrait"]
+        assert (
+            online_response.to_dict()["conv_rate_plus_acc"]
+            == online_response.to_dict()["conv_rate_plus_acc_substrait"]
         )