[Bella-Xiang]

The specialized vector database performs well when processing pure vector tasks but performs badly when it comes to SQL compatibility and integration with the existing system; And the traditional database with vector algorithm or vector plug-in like ES, PG, and Redis, achieves the vector function, the advantage is that it is very easy to create tasks in a production environment, but when the data scale is relatively large, they will quickly encounter performance bottlenecks.

There is a new type of vector database that combines the best of both worlds, which is MyScale, the SQL vector database. You can refer to the following blogs to see the comparison. our comprehensive benchmark evaluation reveals that MyScale exceeds other products in terms of filtered vector search accuracy, performance, cost-efficiency, and index build time by a long way. Importantly, MyScale is the only product tested that delivers healthy search accuracy and QPS across various filter ratios.

https://myscale.com/blog/myscale-outperform-specialized-vect... https://myscale.com/blog/myscale-vs-postgres-opensearch/