[lmeyerov]

It's funny taking a numbers view. The most popularly used might not even be these, but vector indexes in existing popular OSS DBs and storage systems people are already using. Afaict earliest would be faiss on disk and vectors in opensearch & elasticsearch, and I'd be curious how say databricks, pgvector and other big ones are getting picked up now that they are out. Most of these supported fast & large-scale indexes even early on (ivfpq, ...) by wrapping faiss and friends. ~All OSS DBs we use now, esp managed, have or are getting vector indexes.

Another one most similar to qdrant we track internally is lancedb. They are clever by supporting an embedded architecture, so an architectural reason to prefer over most existing OSS DBs. In our survey 2 years ago, we predicted specialized vector DBs having regular OSS DBs be the elephant in the room, and missed embedded as a fundamentally different category: https://gradientflow.com/the-vector-database-index/ .

(Good luck to qdrant! I'm happy they waited before raising, hopefully this means they can operate more healthily than otherwise and easier to maintain the discipline to do that!)