Build Sql And Vector Retrieval Context Layers With Tidb
ASecurity
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.
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---
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](https://agentskillexchange.com/skills/build-sql-and-vector-retrieval-context-layers-with-tidb/)
