pgvectorvsqdrant
pgvector adds vector search to existing Postgres — zero new infra. Qdrant is purpose-built for vectors at scale with filtering and quantization. Pick pgvector for <10M vectors, Qdrant beyond.
pgvector
github.com/pgvector/pgvectorVector search inside Postgres. ~12k stars and dominant in 2026 as the boring-but-correct default. If you already have Postgres (Supabase, Neon, RDS), do not add another database — just install this extension. Works for the vast majority of RAG apps.
Full review →qdrant
github.com/qdrant/qdrantRust-based vector database — fast, production-grade, Apache 2.0. Good developer experience and clear pricing if you use their managed cloud. Strong choice if Postgres+pgvector cannot handle your scale.
Full review →Which should you pick?
Pick pgvector if…
You are already on Postgres and want vector search without operating a second database.
Skip pgvector if…
You need billion-scale vector search with millisecond latency — a dedicated vector DB is worth the operational cost.
Pick qdrant if…
You need production-grade vector search at scale and Postgres is hitting limits.
Skip qdrant if…
You are starting fresh on Postgres — pgvector is enough for most apps.
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