diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py
index aabbb91a7..eb9011e5f 100644
--- a/src/backend/base/langflow/components/vectorstores/AstraDB.py
+++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py
@@ -137,7 +137,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
         ),
     ]
 
-    def build_vector_store(self):
+    def _build_vector_store_no_ingest(self):
         try:
             from langchain_astradb import AstraDBVectorStore
             from langchain_astradb.utils.astradb import SetupMode
@@ -196,11 +196,13 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
         except Exception as e:
             raise ValueError(f"Error initializing AstraDBVectorStore: {str(e)}") from e
 
+        return vector_store
+
+    def build_vector_store(self):
+        vector_store = self._build_vector_store_no_ingest()
         if hasattr(self, "ingest_data") and self.ingest_data:
             logger.debug("Ingesting data into the Vector Store.")
             self._add_documents_to_vector_store(vector_store)
-
-        self.status = self._astradb_collection_to_data(vector_store.collection)
         return vector_store
 
     def _add_documents_to_vector_store(self, vector_store):
@@ -221,7 +223,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
             logger.debug("No documents to add to the Vector Store.")
 
     def search_documents(self) -> list[Data]:
-        vector_store = self.build_vector_store()
+        vector_store = self._build_vector_store_no_ingest()
 
         logger.debug(f"Search input: {self.search_input}")
         logger.debug(f"Search type: {self.search_type}")
@@ -253,13 +255,3 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
         else:
             logger.debug("No search input provided. Skipping search.")
             return []
-
-    def _astradb_collection_to_data(self, collection):
-        data = []
-        data_dict = collection.find()
-        if data_dict and "data" in data_dict:
-            data_dict = data_dict["data"].get("documents", [])
-
-        for item in data_dict:
-            data.append(Data(content=item["content"]))
-        return data
diff --git a/src/backend/base/langflow/components/vectorstores/Cassandra.py b/src/backend/base/langflow/components/vectorstores/Cassandra.py
index 053e06ec0..90800e70b 100644
--- a/src/backend/base/langflow/components/vectorstores/Cassandra.py
+++ b/src/backend/base/langflow/components/vectorstores/Cassandra.py
@@ -102,9 +102,9 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
     ]
 
     def build_vector_store(self) -> Cassandra:
-        return self._build_cassandra()
+        return self._build_cassandra(ingest=True)
 
-    def _build_cassandra(self) -> Cassandra:
+    def _build_cassandra(self, ingest: bool) -> Cassandra:
         try:
             import cassio
         except ImportError:
@@ -142,11 +142,12 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
 
         documents = []
 
-        for _input in self.ingest_data or []:
-            if isinstance(_input, Data):
-                documents.append(_input.to_lc_document())
-            else:
-                documents.append(_input)
+        if ingest:
+            for _input in self.ingest_data or []:
+                if isinstance(_input, Data):
+                    documents.append(_input.to_lc_document())
+                else:
+                    documents.append(_input)
 
         if documents:
             table = Cassandra.from_documents(
@@ -172,7 +173,7 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
         return table
 
     def search_documents(self) -> List[Data]:
-        vector_store = self._build_cassandra()
+        vector_store = self._build_cassandra(ingest=False)
 
         if self.search_query and isinstance(self.search_query, str) and self.search_query.strip():
             try: