diff --git a/langchain/vectorstores/analyticdb.py b/langchain/vectorstores/analyticdb.py
index d8986aeffa..86917b628f 100644
--- a/langchain/vectorstores/analyticdb.py
+++ b/langchain/vectorstores/analyticdb.py
@@ -49,6 +49,7 @@ class AnalyticDB(VectorStore):
         collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
         pre_delete_collection: bool = False,
         logger: Optional[logging.Logger] = None,
+        engine_args: Optional[dict] = None,
     ) -> None:
         self.connection_string = connection_string
         self.embedding_function = embedding_function
@@ -56,15 +57,26 @@ class AnalyticDB(VectorStore):
         self.collection_name = collection_name
         self.pre_delete_collection = pre_delete_collection
         self.logger = logger or logging.getLogger(__name__)
-        self.__post_init__()
+        self.__post_init__(engine_args)
 
     def __post_init__(
         self,
+        engine_args: Optional[dict] = None,
     ) -> None:
         """
         Initialize the store.
         """
-        self.engine = create_engine(self.connection_string)
+
+        _engine_args = engine_args or {}
+
+        if (
+            "pool_recycle" not in _engine_args
+        ):  # Check if pool_recycle is not in _engine_args
+            _engine_args[
+                "pool_recycle"
+            ] = 3600  # Set pool_recycle to 3600s if not present
+
+        self.engine = create_engine(self.connection_string, **_engine_args)
         self.create_collection()
 
     def create_table_if_not_exists(self) -> None:
@@ -324,6 +336,36 @@ class AnalyticDB(VectorStore):
         )
         return [doc for doc, _ in docs_and_scores]
 
+    def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]:
+        """Delete by vector IDs.
+
+        Args:
+            ids: List of ids to delete.
+        """
+        if ids is None:
+            raise ValueError("No ids provided to delete.")
+
+        # Define the table schema
+        chunks_table = Table(
+            self.collection_name,
+            Base.metadata,
+            Column("id", TEXT, primary_key=True),
+            Column("embedding", ARRAY(REAL)),
+            Column("document", String, nullable=True),
+            Column("metadata", JSON, nullable=True),
+            extend_existing=True,
+        )
+
+        try:
+            with self.engine.connect() as conn:
+                with conn.begin():
+                    delete_condition = chunks_table.c.id.in_(ids)
+                    conn.execute(chunks_table.delete().where(delete_condition))
+                    return True
+        except Exception as e:
+            print("Delete operation failed:", str(e))
+            return False
+
     @classmethod
     def from_texts(
         cls: Type[AnalyticDB],
@@ -334,6 +376,7 @@ class AnalyticDB(VectorStore):
         collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
         ids: Optional[List[str]] = None,
         pre_delete_collection: bool = False,
+        engine_args: Optional[dict] = None,
         **kwargs: Any,
     ) -> AnalyticDB:
         """
@@ -351,6 +394,7 @@ class AnalyticDB(VectorStore):
             embedding_function=embedding,
             embedding_dimension=embedding_dimension,
             pre_delete_collection=pre_delete_collection,
+            engine_args=engine_args,
         )
 
         store.add_texts(texts=texts, metadatas=metadatas, ids=ids, **kwargs)
@@ -382,6 +426,7 @@ class AnalyticDB(VectorStore):
         collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
         ids: Optional[List[str]] = None,
         pre_delete_collection: bool = False,
+        engine_args: Optional[dict] = None,
         **kwargs: Any,
     ) -> AnalyticDB:
         """
@@ -405,6 +450,7 @@ class AnalyticDB(VectorStore):
             metadatas=metadatas,
             ids=ids,
             collection_name=collection_name,
+            engine_args=engine_args,
             **kwargs,
         )
 
diff --git a/tests/integration_tests/vectorstores/test_analyticdb.py b/tests/integration_tests/vectorstores/test_analyticdb.py
index 1149b2259b..c8ce1c9bb0 100644
--- a/tests/integration_tests/vectorstores/test_analyticdb.py
+++ b/tests/integration_tests/vectorstores/test_analyticdb.py
@@ -47,6 +47,22 @@ def test_analyticdb() -> None:
     assert output == [Document(page_content="foo")]
 
 
+def test_analyticdb_with_engine_args() -> None:
+    engine_args = {"pool_recycle": 3600, "pool_size": 50}
+    """Test end to end construction and search."""
+    texts = ["foo", "bar", "baz"]
+    docsearch = AnalyticDB.from_texts(
+        texts=texts,
+        collection_name="test_collection",
+        embedding=FakeEmbeddingsWithAdaDimension(),
+        connection_string=CONNECTION_STRING,
+        pre_delete_collection=True,
+        engine_args=engine_args,
+    )
+    output = docsearch.similarity_search("foo", k=1)
+    assert output == [Document(page_content="foo")]
+
+
 def test_analyticdb_with_metadatas() -> None:
     """Test end to end construction and search."""
     texts = ["foo", "bar", "baz"]
@@ -126,3 +142,25 @@ def test_analyticdb_with_filter_no_match() -> None:
     )
     output = docsearch.similarity_search_with_score("foo", k=1, filter={"page": "5"})
     assert output == []
+
+
+def test_analyticdb_delete() -> None:
+    """Test end to end construction and search."""
+    texts = ["foo", "bar", "baz"]
+    ids = ["fooid", "barid", "bazid"]
+    metadatas = [{"page": str(i)} for i in range(len(texts))]
+    docsearch = AnalyticDB.from_texts(
+        texts=texts,
+        collection_name="test_collection_delete",
+        embedding=FakeEmbeddingsWithAdaDimension(),
+        metadatas=metadatas,
+        connection_string=CONNECTION_STRING,
+        ids=ids,
+        pre_delete_collection=True,
+    )
+    output = docsearch.similarity_search_with_score("foo", k=1, filter={"page": "2"})
+    print(output)
+    assert output == [(Document(page_content="baz", metadata={"page": "2"}), 4.0)]
+    docsearch.delete(ids=ids)
+    output = docsearch.similarity_search_with_score("foo", k=1, filter={"page": "2"})
+    assert output == []