build-sql-and-vector-retrieval-context-layers-with-tidb

name	Build SQL and vector retrieval context layers with TiDB
slug	build-sql-and-vector-retrieval-context-layers-with-tidb
description	Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.
github_stars	40235
verification	listed
source	https://github.com/pingcap/tidb
author	PingCAP
publisher_type	organization
category	Data Extraction & Transformation
framework	Multi-Framework
tool_ecosystem	{"github_repo":"pingcap/tidb","github_stars":40235}

Build SQL and vector retrieval context layers with TiDB

Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.

Prerequisites

TiDB or TiDB Cloud, an embedding model, SQL client or application connector, source documents or application records

Installation

No source-backed install or usage instructions could be extracted automatically. Review the upstream project before running this skill in a sensitive workflow.

• Source: https://github.com/pingcap/tidb

Documentation

• https://docs.pingcap.com/tidb/stable/vector-search-overview/

Source

• Agent Skill Exchange