Strongly disagree with PGVector's DX being worse than Chroma. Installing, configuring, and working with Chroma was infuriating -- it's alpha software and has the bugs and rough edges to prove it. The tools to support and interface with postgres are battle-tested and so much nicer by comparison; getting Chroma working took over a week, ripping it out and replacing with PGVector took a couple hours.

Also agree with this[0] article that vector search is only one type of search, and even for RAG isn't necessarily the one you want to start with.

[0]: https://colinharman.substack.com/p/beware-tunnel-vision-in-a...

I don't think we need specialized databases for vectors. Relational databases can easily be expanded by vector data types and operations. They will eventually catch up by supporting what was once a unique feature of the new system: https://medium.com/@magda7817/two-things-to-keep-in-mind-bef...

None of these vector dbs seem economical outside of enterprise.

I've been wondering about Redis as vector database [0].

[0]: https://twitter.com/sh_reya/status/1661136833848438784

16x difference between pg and milvus?

I thought for most use cases this would be quite performance sensitive

Their definition about Hybrid Search is I think wrong.

Through this terms tend to not be consistently defined at all, so "wrong" is maybe the wrong word.

Their definition seem to be about filtering results during (approximate) KNN vector search.

But that is filtering, not hybrid search. Through it might sometimes be implemented as a form of hybrid search, but that's an internal implementation detail and you probably should hope it's not implemented that way.

Hybrid search is when you do both a vector search and a more classical text based search (e.g. bm25) and combine both results in a reasonable way.

I'm curious where got the numbers on qps? They are pretty different from our experience. Reached out on LinkedIn. ;)

Curious about the lack of Vespa, especially given the thoroughness of the article and its long-time reputation. OpenSearch is also missing, but perhaps it can be considered being lumped in with Elasticsearch due to them both being based on Lucene. The products are starting to diverge, so would be nice to see, especially since it is open-source.

For the performance-based columns, would be also helpful to see which versions were tested. There is so much attention lately for vector databases, that they all are making great strides forward. The Lucene updates are notable.

I'm actually curious on how the new vector DB from cloudflare compares.