Pyyan / Compare / Milvus vs pgvector vs Pinecone vs Weaviate

Milvus vs pgvector vs Pinecone vs Weaviate

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Vector Databases · verified 13 Aug 2026

×MilvusZillizcurrent
×pgvectorPostgreSQLcurrent
×PineconePineconecurrent
×WeaviateWeaviatecurrent
1 slot left
SpecificationMilvuspgvectorPineconeWeaviate
SummaryBuilt for billions of vectors.Vectors inside the database you already run.Managed, and the smoothest to operate.Hybrid search with batteries included.
IndexHNSW, IVF, DiskANN, GPUHNSW, IVFFlatProprietaryHNSW
Hybrid searchYesYes, with SQLYesYes, native
HostingSelf-host and managedSelf-host or any managed PostgresManaged onlySelf-host and managed
LicenceApache 2.0PostgreSQLProprietaryBSD-3
p50 latency~10ms~15ms<10ms~12ms
CategoryVector DatabasesVector DatabasesVector DatabasesVector Databases
OfficialZillizPostgreSQLPineconeWeaviate

Highlighted rows are where these differ.

Milvus

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

Best for very large corpora.

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 →

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 →