As another signal, check out this report by Streamlit, which shows the popularity of different vector databases among Streamlit apps: https://state-of-llm.streamlit.app/#third

Faiss and Pinecone are at the top (disclosure: I'm from Pinecone). But Faiss isn't really a full-fledged vector DB. Pinecone is a managed option which is out of the question for a company like Twitter and maybe for you (although you should consider it). After that comes Chroma in third, and then Qdrant, and then Weaviate.

Chroma has a big following by virtue of being plugged into the AI ecosystem in SF. Qdrant seems to be doing great work but their location in Europe is probably not helping.

We've been using qdrant in production for over a year. It's excellent and the team are very responsive to the few issues we've had. Qdrant does one job and scales well.

I've been using pgvector, it has worked as expected, which is all I want. Personally my choice was based entirely on the fact that I already use postgres, and that it will still probably exist in it's current form after the dust settles on the vector db market.

(disclosure: I work at Weaviate) I think it depends on your use-case. From what I've seen, Weaviate and Qdrant have similar offerings in terms of features, open-sourceness, flexible deployment, and integrations with other services. Weaviate does provide certain things easier to set up, like built-in hybrid search, modules for integrations, vectorization, etc. (so it's just a one-line config change), and it's all custom-built from the ground up. But Qdrant gets a lot of support from the Rust community and has a slightly more flexible free cloud tier.

Also, don't believe everything posted on the internet ;)