Vector Database Comparison

Compare the leading vector databases for your AI application.

Feature Pinecone Weaviate Qdrant Milvus Chroma pgvector
TypeManagedOpen/ManagedOpen/ManagedOpenOpenExtension
Self-hostNoYesYesYesYesYes
Free tierYesYesYes-UnlimitedFree
IndexProprietaryHNSWHNSWMultipleHNSWIVFFlat/HNSW
FilteringGoodExcellentExcellentGoodBasicFull SQL
Hybrid searchYesYesYesYesNoWith pg
Best forProductionHybrid/GraphQLPerformanceScaleDev/ProtoPostgres users

Quick Recommendations

Just starting / Prototyping

Chroma

Runs locally, no setup, great DX

Production (managed)

Pinecone

Zero ops, enterprise support

Self-hosted performance

Qdrant

Fast, great filtering, Rust

Already using Postgres

pgvector

No new infrastructure

Detailed Notes

Pinecone

Fully managed, easiest to use. Great for teams that don't want to manage infrastructure. Pricing can add up at scale.

Weaviate

Powerful hybrid search, GraphQL API, built-in vectorization. More complex but very capable.

Qdrant

Written in Rust, excellent performance. Great filtering capabilities. Growing community.

Milvus

Enterprise-scale, many index types. More complex to operate. Good for very large datasets.

Chroma

Perfect for local development and prototyping. Simple API, runs in-process. Limited production features.

pgvector

If you use Postgres, start here. Keep vectors with relational data. May not scale as well as dedicated solutions.