Pyyan / Compare / Pinecone vs pgvector vs Milvus vs Weaviate

Pinecone vs pgvector vs Milvus vs Weaviate

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Vector Databases · verified 13 Aug 2026

×PineconePineconecurrent
×pgvectorPostgreSQLcurrent
×MilvusZillizcurrent
×WeaviateWeaviatecurrent
1 slot left
SpecificationPineconepgvectorMilvusWeaviate
SummaryManaged, and the smoothest to operate.Vectors inside the database you already run.Built for billions of vectors.Hybrid search with batteries included.
IndexProprietaryHNSW, IVFFlatHNSW, IVF, DiskANN, GPUHNSW
Hybrid searchYesYes, with SQLYesYes, native
HostingManaged onlySelf-host or any managed PostgresSelf-host and managedSelf-host and managed
LicenceProprietaryPostgreSQLApache 2.0BSD-3
p50 latency<10ms~15ms~10ms~12ms
CategoryVector DatabasesVector DatabasesVector DatabasesVector Databases
OfficialPineconePostgreSQLZillizWeaviate

Highlighted rows are where these differ.

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 →

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 →

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 →