Which vector database has the best performance benchmarks?

Benchmark results depend heavily on dataset size, dimensionality, recall target, and hardware, so no single database wins universally. Qdrant and Milvus typically lead on query throughput and indexing speed in public benchmarks like ANN Benchmarks and the Qdrant vector-db-benchmark. Pinecone optimizes latency for serverless workloads with cold-start trade-offs. pgvector with HNSW lags dedicated databases on raw speed but wins on integration simplicity. Always run benchmarks on your own data distribution since synthetic datasets rarely predict production performance.