Pyyan / Compare / pgvector vs Pinecone vs Milvus vs Weaviate

pgvector vs Pinecone vs Milvus vs Weaviate

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Vector Databases · verified 13 Aug 2026

×pgvectorPostgreSQLcurrent
×PineconePineconecurrent
×MilvusZillizcurrent
×WeaviateWeaviatecurrent
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SpecificationpgvectorPineconeMilvusWeaviate
SummaryVectors inside the database you already run.Managed, and the smoothest to operate.Built for billions of vectors.Hybrid search with batteries included.
IndexHNSW, IVFFlatProprietaryHNSW, IVF, DiskANN, GPUHNSW
Hybrid searchYes, with SQLYesYesYes, native
HostingSelf-host or any managed PostgresManaged onlySelf-host and managedSelf-host and managed
LicencePostgreSQLProprietaryApache 2.0BSD-3
p50 latency~15ms<10ms~10ms~12ms
CategoryVector DatabasesVector DatabasesVector DatabasesVector Databases
OfficialPostgreSQLPineconeZillizWeaviate

Highlighted rows are where these differ.

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 →

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 →