Pyyan / Compare / Weaviate vs Qdrant vs Milvus

Weaviate vs Qdrant vs Milvus

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Vector Databases · verified 13 Aug 2026

×WeaviateWeaviatecurrent
×QdrantQdrantcurrent
×MilvusZillizcurrent
2 slots left
SpecificationWeaviateQdrantMilvus
SummaryHybrid search with batteries included.The fastest of the purpose-built stores.Built for billions of vectors.
IndexHNSWHNSWHNSW, IVF, DiskANN, GPU
Hybrid searchYes, nativeYesYes
HostingSelf-host and managedSelf-host and managedSelf-host and managed
LicenceBSD-3Apache 2.0Apache 2.0
p50 latency~12ms4ms~10ms
CategoryVector DatabasesVector DatabasesVector Databases
OfficialWeaviateQdrantZilliz

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 →

Qdrant

  • Written in Rust; 10 to 25% faster than Weaviate or Milvus on common workloads
  • Strong filtering alongside vector search
  • Self-host or managed, same engine

Best for latency-sensitive retrieval.

Full spec sheet →

Milvus

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

Best for very large corpora.

Full spec sheet →