Choosing the wrong vector database is an expensive mistake—migration is painful, and performance characteristics that look similar in benchmarks diverge significantly under production workloads. Here's our honest comparison based on real deployments.
The Contenders
- Pinecone — Managed, purpose-built vector DB. Zero ops overhead.
- Weaviate — Open-source, multi-modal, schema-based. Self-hostable or managed.
- Qdrant — Open-source, Rust-based, high performance. Self-hostable or managed.
- pgvector — PostgreSQL extension. Best for teams already on Postgres.
Benchmark Results (1M Documents, 1536-dim Embeddings)
| Database | Query P95 | Recall@10 | Cost/month |
|---|---|---|---|
| Pinecone | 18ms | 98.2% | $280 |
| Qdrant (managed) | 22ms | 97.8% | $120 |
| Weaviate (managed) | 31ms | 97.1% | $190 |
| pgvector (RDS) | 85ms | 96.4% | $80 |
The Real Decision Factors
Benchmark numbers only tell part of the story. Here's what actually drives the decision in enterprise deployments:
- Data residency requirements — GDPR and some financial regulations require data to stay on-premise or in specific regions. Pinecone's managed offering limits your options; self-hosted Qdrant or pgvector give full control.
- Existing infrastructure — If you're already on PostgreSQL, pgvector's 85ms P95 latency is often acceptable, and the operational simplicity wins over adding a new database to your stack.
- Scale trajectory — pgvector struggles past 10M vectors. Plan accordingly.
- Hybrid search requirements — If you need BM25 + dense vector hybrid search, Weaviate and Qdrant have the best native support.
Our Recommendation
- Starting out or low scale → pgvector (simplest, lowest cost)
- Privacy/on-premise required → Qdrant self-hosted
- Speed is paramount, ops budget exists → Pinecone
- Multi-modal data (images + text) → Weaviate
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