# RooAGI Releases Roo-VectorDB: A High-Performance PostgreSQL Extension for Vector Search **URL:** \ **Category:** Community Extensions & Builds\ **Tags:** new-release\ **Created:** [July 18, 2025, 4:47pm UTC](https://forums.percona.com/t/rooagi-releases-roo-vectordb-a-high-performance-postgresql-extension-for-vector-search/38741 "2025-07-18T16:47:24Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![RooAGI](https://avatars.discourse-cdn.com/v4/letter/r/bb73d2/32.png) [@RooAGI](https://forums.percona.com/u/RooAGI)\ **Post date:** [July 18, 2025, 4:47pm UTC](https://forums.percona.com/t/rooagi-releases-roo-vectordb-a-high-performance-postgresql-extension-for-vector-search/38741/1 "2025-07-18T16:47:24Z")
RooAGI ([https://rooagi.com](https://rooagi.com)) has released Roo-VectorDB, a PostgreSQL extension designed as a high-performance storage solution for high-dimensional vector data. Check it out on GitHub: [GitHub - RooAGI/Roo-VectorDB: Roo-VectorDB is a powerful vector database built as an extension on top of PostgreSQL.](https://github.com/RooAGI/Roo-VectorDB) We chose to build on PostgreSQL because of its readily available metadata search capabilities and proven scalability as a relational database. While PGVector has pioneered this approach, it’s often perceived as slower than native vector databases like Milvus. Roo-VectorDB builds on the PGVector framework, incorporating our own optimizations in search strategies, memory management, and support for higher-dimensional vectors. In preliminary lab testing using [ANN-Benchmarks](https://github.com/erikbern/ann-benchmarks), Roo-VectorDB demonstrated performance that was comparable to, or significantly better than, Milvus in terms of QPS (queries per second). RooAGI will continue to develop AI-focused products, with Roo-VectorDB as a core storage component in our stack. We invite developers around the world to try out the current release and share feedback. Discussions are welcome in [r/RooAGI](https://www.reddit.com/r/RooAGI/)