We chose to build on PostgreSQL because of its readily available metadata search capabilities and proven scalability of relational databases. 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-Benchmark, 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.