Pyyan / Compare / LanceDB vs pgvector vs Pinecone vs Milvus

LanceDB vs pgvector vs Pinecone vs Milvus

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Vector Databases · verified 13 Aug 2026

×LanceDBLanceDBcurrent
×pgvectorPostgreSQLcurrent
×PineconePineconecurrent
×MilvusZillizcurrent
1 slot left
SpecificationLanceDBpgvectorPineconeMilvus
SummaryEmbedded, multimodal, columnar.Vectors inside the database you already run.Managed, and the smoothest to operate.Built for billions of vectors.
IndexIVF-PQ, HNSWHNSW, IVFFlatProprietaryHNSW, IVF, DiskANN, GPU
Hybrid searchYesYes, with SQLYesYes
HostingEmbedded and managedSelf-host or any managed PostgresManaged onlySelf-host and managed
LicenceApache 2.0PostgreSQLProprietaryApache 2.0
p50 latencyVaries~15ms<10ms~10ms
CategoryVector DatabasesVector DatabasesVector DatabasesVector Databases
OfficialLanceDBPostgreSQLPineconeZilliz

Highlighted rows are where these differ.

LanceDB

  • Lance columnar format, versioned like a table
  • Runs in-process, no service to operate

Best for multimodal data and local apps.

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 →