diff --git a/cognee/modules/data/deletion/prune_system.py b/cognee/modules/data/deletion/prune_system.py
index 66f93ec48..b5d944dbb 100644
--- a/cognee/modules/data/deletion/prune_system.py
+++ b/cognee/modules/data/deletion/prune_system.py
@@ -1,3 +1,5 @@
+from sqlalchemy.exc import OperationalError
+
 from cognee.context_global_variables import backend_access_control_enabled
 from cognee.infrastructure.databases.vector import get_vector_engine
 from cognee.infrastructure.databases.graph.get_graph_engine import get_graph_engine
@@ -6,6 +8,9 @@ from cognee.infrastructure.databases.vector.config import get_vectordb_config
 from cognee.infrastructure.databases.graph.config import get_graph_config
 from cognee.shared.cache import delete_cache
 from cognee.modules.users.models import DatasetDatabase
+from cognee.shared.logging_utils import get_logger
+
+logger = get_logger()
 
 
 async def prune_graph_databases():
@@ -19,11 +24,18 @@ async def prune_graph_databases():
         return await handler["handler_instance"].delete_dataset(dataset_database)
 
     db_engine = get_relational_engine()
-    if "dataset_database" in await db_engine.get_table_names():
-        data = await db_engine.get_all_data_from_table("dataset_database")
-        # Go through each dataset database and delete the graph database
-        for data_item in data:
-            await _prune_graph_db(data_item)
+    try:
+        if "dataset_database" in await db_engine.get_table_names():
+            data = await db_engine.get_all_data_from_table("dataset_database")
+            # Go through each dataset database and delete the graph database
+            for data_item in data:
+                await _prune_graph_db(data_item)
+    except OperationalError as e:
+        logger.debug(
+            "Skipping pruning of graph DB. OperationalError when accessing dataset_database table: %s",
+            e,
+        )
+        return
 
 
 async def prune_vector_databases():
@@ -38,11 +50,18 @@ async def prune_vector_databases():
         return await handler["handler_instance"].delete_dataset(dataset_database)
 
     db_engine = get_relational_engine()
-    if "dataset_database" in await db_engine.get_table_names():
-        data = await db_engine.get_all_data_from_table("dataset_database")
-        # Go through each dataset database and delete the vector database
-        for data_item in data:
-            await _prune_vector_db(data_item)
+    try:
+        if "dataset_database" in await db_engine.get_table_names():
+            data = await db_engine.get_all_data_from_table("dataset_database")
+            # Go through each dataset database and delete the vector database
+            for data_item in data:
+                await _prune_vector_db(data_item)
+    except OperationalError as e:
+        logger.debug(
+            "Skipping pruning of vector DB. OperationalError when accessing dataset_database table: %s",
+            e,
+        )
+        return
 
 
 async def prune_system(graph=True, vector=True, metadata=True, cache=True):