Honest comparison of pgvector, Pinecone, Turbopuffer, and Qdrant in 2026. Real latency numbers, pricing math, and which vector database to pick.

Alex CloudStar

A hands-on comparison of four vector databases — pgvector, Pinecone, Turbopuffer, and Qdrant — tested against a real RAG workload of 2 million vectors at ~1,000 queries/day. Key findings: pgvector wins on cost and simplicity for under 10M vectors if you're already on Postgres (8–25ms p95, ~$30/mo); Qdrant leads on hybrid search and filtering (15–40ms p95, ~$40–80/mo); Turbopuffer offers dramatically lower cost for large corpora but has cold-query latency (300–800ms); Pinecone remains the easiest managed option but costs ~$180/mo at this scale. The author migrated from Pinecone to pgvector for their main workload, kept Qdrant for hybrid search needs, and uses Turbopuffer for a large document archive.

pgvector vs Pinecone vs Turbopuffer vs Qdrant (2026)

pgvector: The Boring Winner For Most Projects

Pinecone: The Managed Option That Used To Be The Default