Pyyan / Compare / Weaviate vs pgvector vs Pinecone vs Milvus

Weaviate vs pgvector vs Pinecone vs Milvus

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Vector Databases · verified 13 Aug 2026

×WeaviateWeaviatecurrent
×pgvectorPostgreSQLcurrent
×PineconePineconecurrent
×MilvusZillizcurrent
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SpecificationWeaviatepgvectorPineconeMilvus
SummaryHybrid search with batteries included.Vectors inside the database you already run.Managed, and the smoothest to operate.Built for billions of vectors.
IndexHNSWHNSW, IVFFlatProprietaryHNSW, IVF, DiskANN, GPU
Hybrid searchYes, nativeYes, with SQLYesYes
HostingSelf-host and managedSelf-host or any managed PostgresManaged onlySelf-host and managed
LicenceBSD-3PostgreSQLProprietaryApache 2.0
p50 latency~12ms~15ms<10ms~10ms
CategoryVector DatabasesVector DatabasesVector DatabasesVector Databases
OfficialWeaviatePostgreSQLPineconeZilliz

Highlighted rows are where these differ.

Weaviate

  • Vector, BM25 and metadata filters in one query
  • Modules for embedding generation built in

Best for hybrid keyword and semantic search.

Full spec sheet →

pgvector

  • One database for vectors, rows and joins
  • The honest default: reach for something else only when this stops working

Best for almost everyone, until scale says otherwise.

Full spec sheet →

Pinecone

  • Sub-10ms p50 with nothing to maintain
  • Costs draw scrutiny at scale; Notion moved away and cut spend ~60%

Best for teams who do not want to run a database.

Full spec sheet →

Milvus

  • Distributed architecture with GPU index support
  • Heavier to operate than the alternatives

Best for very large corpora.

Full spec sheet →