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Qdrant

Vector database written in Rust. Strong filtering (payload-based pre-filter), HNSW index with quantization variants, gRPC + REST APIs. The performance pick when you cross 10M vectors.

By Fredoline Eruo·Last verified May 6, 2026·24,000 GitHub stars

Overview

Vector database written in Rust. Strong filtering (payload-based pre-filter), HNSW index with quantization variants, gRPC + REST APIs. The performance pick when you cross 10M vectors.

Stack & relationships

How Qdrant relates to other entries in the catalog — recommended pairings, alternatives, dependencies, and edges to avoid. Each edge carries a one-line operator note from our editorial team.

Qdrant ↔ ecosystem

Works with

  • Works with
    AnythingLLM

    The upgrade path when workspaces grow past 100K vectors. PQ quantization cuts storage 4-8x.

  • Works with
    Mem0 (agent memory API)

    Mem0's production-tier vector backend. Switch from LanceDB to Qdrant when memory store grows past ~500K vectors per agent.

  • Works with
    AnythingLLM

    Production-tier swap for AnythingLLM workspaces past 100K vectors. Standard upgrade path.

Alternatives

  • Competes with
    Weaviate

    Both are production-grade vector DBs. Qdrant has the simpler ops surface and better single-node performance; Weaviate has hybrid-search and broader query language.

  • Competes with
    Milvus

    Qdrant is single-node-friendly and fast to deploy; Milvus is the heavy-duty distributed option for the 100M+ vector scale.

  • Alternative to
    Chroma

    Chroma is the simplest dev-experience vector store; Qdrant is the production upgrade once your collection sizes outgrow Chroma's single-node design.

  • Alternative to
    Weaviate

    Weaviate has hybrid search and a richer query language; Qdrant has cleaner ops and faster single-node performance. Pick by workload shape.

  • Alternative to
    Milvus

    Milvus targets 100M+ vector scale with distributed deployment; Qdrant is single-node-friendly. Switch from Qdrant to Milvus only when you've outgrown single-node.

  • Alternative to
    Redis (vector search)

    Redis Vector is the right choice when you already run Redis for caching and want vector search without adding another service. Slower than purpose-built vector DBs at scale.

Pros

  • Rust performance
  • Excellent payload filtering
  • Production-grade clustering

Cons

  • Steeper learning curve than Chroma
  • Less mature for graph queries

Compatibility

Operating systems
macOS
Linux
Windows
Docker
GPU backends
optional GPU acceleration
LicenseOpen source · free (OSS) + managed cloud

Get Qdrant

Official site
https://qdrant.tech
GitHub
https://github.com/qdrant/qdrant

Frequently asked

Is Qdrant free?

Qdrant has a paid tier (free (OSS) + managed cloud). Check the pricing page for current terms.

What operating systems does Qdrant support?

Qdrant supports macOS, Linux, Windows, Docker.

Which GPUs work with Qdrant?

Qdrant supports optional GPU acceleration. CPU-only inference is also possible but slow.

Reviewed by RunLocalAI Editorial. See our editorial policy for how we evaluate tools.