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Choosing vector database: a side-by-side comparison

benchmark.vectorview.ai

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Re: Choosing vector database: a side-by-side comparison

#121
Postgres with PGVector is the best database, plus vectors.

All of the "Vector DBs" suffer horribly when trying to do basic things.

Want to include any field that matches a field in an array of keys? Easy in SQL. Requires an entire song and dance in Pinecone or Weaviate.

After implementing Chroma, Weaviate, Pinecone, Sqlite with HNSW indices and Qdrant-- I'm not impressed. Postgres is measurably faster since so much relies on pre-filtering, joins, etc.

Re: Choosing vector database: a side-by-side comparison

#123
Quick question regarding the scalability and support of multiple vector databases under a single cloud service. Suppose an enterprise Saas product served multiple customers with each requiring a unique RAG vector knowledge-base for product and company info. Do any of these solutions allow for a large number (dozens or hundreds) of small distinct Knowledge bases? Do any offer easily integrated automated pipelines for documents to be parsed and ingested?

Re: Choosing vector database: a side-by-side comparison

#124

Postgres with PGVector is the best database, plus vectors. All of the "Vector DBs" suffer horribly when trying to do basic things. Want to include any field that matches a field in an array of keys? Easy in SQL. Requires an entire song and dance in Pinecone or Weaviate. After implementing Chroma, Weaviate, Pinecone, Sqlite with HNSW indices and Qdrant-- I'm not impressed. Postgres is measurably faster since so much r…

This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
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