Vector Search Integration Overview

This document provides an overview of TiDB Vector Search integration, including supported AI frameworks, embedding models, and Object Relational Mapping (ORM) libraries.

Note

TiDB Vector Search is only available for TiDB Self-Managed (TiDB >= v8.4) and TiDB Cloud Serverless. It is not available for TiDB Cloud Dedicated.

AI frameworks

TiDB provides official support for the following AI frameworks, enabling you to easily integrate AI applications developed based on these frameworks with TiDB Vector Search.

AI frameworks	Tutorial
Langchain	Integrate Vector Search with LangChain
LlamaIndex	Integrate Vector Search with LlamaIndex

Moreover, you can also use TiDB for various purposes, such as document storage and knowledge graph storage for AI applications.

AI services

TiDB Vector Search supports integration with the following AI service, enabling you to easily build Retrieval-Augmented Generation (RAG) based applications.

• Amazon Bedrock

Embedding models and services

TiDB Vector Search supports storing vectors of up to 16383 dimensions, which accommodates most embedding models.

You can either use self-deployed open-source embedding models or third-party embedding APIs provided by third-party embedding providers to generate vectors.

The following table lists some mainstream embedding service providers and the corresponding integration tutorials.

Embedding service providers	Tutorial
Jina AI	Integrate Vector Search with Jina AI Embeddings API

Object Relational Mapping (ORM) libraries

You can integrate TiDB Vector Search with your ORM library to interact with the TiDB database.

The following table lists the supported ORM libraries and the corresponding integration tutorials:

Language	ORM/Client	How to install	Tutorial
Python	TiDB Vector Client	pip install tidb-vector[client]	Get Started with Vector Search Using Python
	SQLAlchemy	pip install tidb-vector	Integrate TiDB Vector Search with SQLAlchemy
	peewee	pip install tidb-vector	Integrate TiDB Vector Search with peewee
	Django	pip install django-tidb[vector]	Integrate TiDB Vector Search with Django