diff --git a/CHANGELOG.md b/CHANGELOG.md
index a45bce56b..46567f7b1 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,6 +4,9 @@
 ### Added
 * Added `get_by_name()` method to MetadataOntology object to access both custom and reserved metadata by name.
 
+### Changed
+* `Dataset.create_data_rows()` max limit of DataRows increased to 150,000
+
 # Version 3.33.1 (2022-12-14)
 ### Fixed
 * Fixed where batch creation limit was still limiting # of data rows. SDK should now support creating batches with up to 100k data rows
diff --git a/labelbox/schema/dataset.py b/labelbox/schema/dataset.py
index bdfe02e35..bbabd6259 100644
--- a/labelbox/schema/dataset.py
+++ b/labelbox/schema/dataset.py
@@ -23,8 +23,7 @@
 
 logger = logging.getLogger(__name__)
 
-MAX_DATAROW_PER_API_OPERATION = 150000
-MAX_DATAROW_WITH_METADATA = 30000
+MAX_DATAROW_PER_API_OPERATION = 150_000
 
 
 class Dataset(DbObject, Updateable, Deletable):
@@ -426,15 +425,6 @@ def convert_item(item):
                 f"Cannot create more than {MAX_DATAROW_PER_API_OPERATION} DataRows per function call."
             )
 
-        # TODO: If any datarows contain metadata, we're limiting max # of datarows
-        # until we address performance issues with datarow create with metadata
-        if len(items) > MAX_DATAROW_WITH_METADATA:
-            for row in items:
-                if 'metadata_fields' in row:
-                    raise MalformedQueryException(
-                        f"Cannot create more than {MAX_DATAROW_WITH_METADATA} DataRows, if any DataRows contain metadata"
-                    )
-
         with ThreadPoolExecutor(file_upload_thread_count) as executor:
             futures = [executor.submit(convert_item, item) for item in items]
             items = [future.result() for future in as_completed(futures)]