Benchmarking Vector search in six database engines

Percona benchmarked HNSW vector search in six engines on 990,000 OpenAI embeddings, in one run on one machine. Time to a queryable index ranged from 1.9 minutes to 6.7 hours. pgvector scaled 21.7× at 32 clients, while the three InnoDB-based engines stayed flat. At 1% filter selectivity, pgvector's default returned too few rows. Concurrency figures for those three are partly withdrawn because of a harness lock, and three churn cells are missing.