Does this still hold?
For people who run thousands of QPS on billions of vectors, Milvus is a solid choice. For someone playing with a twitter demo with a few thousand vectors, any vector db can do the job well. In fact there is a fun project Milvus Lite designed for that case :)
I've seen many builders migrate from pgvector to Milvus as their apps scale. But perhaps they wish they had considered scalability earlier.
(I'm from Milvus so i could be biased.)
We dropped milvus after they started trying for force their zilliz garbage saas down our throats.
Interesting, I guess we're on the same page ;)
Then, what if you want hybrid search, or different IVF variants, or disk-based search, or horizontal scaling, or something that leverages SIMD, or sparse vectors? Milvus is great.
Shameless plug: https://github.com/jankovicsandras/plpgsql_bm25 BM25 search implemented in PL/pgSQL ( Unlicense / Public domain )
The repo includes plpgsql_bm25rrf.sql : PL/pgSQL function for hybrid search ( plpgsql_bm25 + pgvector ) with Reciprocal Rank Fusion; and Jupyter notebook examples.
Like others have already said, pgvector is used a lot as well
