The good news is that this already exists in the Redis search module [1], which allows you to do similarity search against indexed embeddings, among other features, and offers comparable performance against other ANN libraries [2], depending on your performance criteria.
I've been using it for a side project to do semantic search on books[3] and have been really happy with its performance. (Not affiliated with any of this, was mostly interested in exploring existing well-performing, fairly standard tools with low latency)
[1] https://redis.io/docs/interact/search-and-query/search/vecto... [2] https://ann-benchmarks.com/#redisearch [3] https://viberary.pizza/how
Re:Do we think about vector dbs wrong?
by neeleshs on Tuesday September 05, 2023 @09:43AM
(#37391531)
Bit of a side note on Redis Search. While performance is pretty good, it is not production quality yet, mostly around monitoring indexing errors and quirky query results. Silent indexing errors pretty much make it impossible to use it in production, especially for structured data.
Re:Do we think about vector dbs wrong?
by manishsharan on Tuesday September 05, 2023 @07:34AM
(#37390340)
Redis Enterprise edition does have Vector database.i haven't used it but am curious about other people's experiences.
Build protocols, not products! I tell people.
It's a terrible advice actually, unless you like eating noodles and scraping by. But it's still the right way.
We're still waiting for the antirez' Redis version of Vector DBs. Maybe he should do one! :)