Most prominent for a surprising amount of the vendors we looked at last year (https://gradientflow.com/the-vector-database-index/ https://gradientflow.com/the-v

Most prominent for a surprising amount of the vendors we looked at last year (https://gradientflow.com/the-vector-database-index/ https://gradientflow.com/the-vector-database-index/): - We would have paid more for storing billion+ rows in-memory than our gov & enterprise customers were paying for a full product. Since then, ivfpq etc have gotten more popular to do responsive searches for bigger-than-memory datasets. If we needed small in-memory workloads, we could have done faiss+pandas+fastapi and moved on. - Vendors pitched themselves as managed databases yet their users complain about them going down & losing data - Many did not support basic search operators: time filtering, ... - Few/none had real modern security, e.g., row-level multi-tenant ABAC I haven't been tracking on a per-vendor basis as each publicizes making piecemeal progress on these. We found one that did #1-3 without failing us yet, and we're biting the bullet to implement #4. A scalable OSS answer to #4 might be the one that causes us to switch.