Qdrant

Platform

Open-source vector search engine, self-hosted or on Qdrant Cloud

Fiyat: Free tier, then paid
Erişim: API key (optional when self-hosted)

Hakkında

Vector database written in Rust for dense, sparse and multi-vector search with payload filtering. Run the Apache-2.0 engine yourself with Docker, or use Qdrant Cloud, which has a free 1 GB cluster and optional hosted embedding inference.

Neler yapabilirsin

Store embeddings and retrieve the nearest matches for RAG and semantic search
Combine dense and sparse (BM25) vectors in one hybrid search query
Filter vector results by metadata such as user, date or category

Başlarken

Start Qdrant with Docker or create a free Qdrant Cloud cluster
Create a collection with a vector size and distance metric
Upsert points and query the nearest neighbours

Örnek kod

docker run -d -p 6333:6333 qdrant/qdrant
curl -X PUT http://localhost:6333/collections/test_collection \
  -H 'Content-Type: application/json' \
  --data-raw '{"vectors": {"size": 4, "distance": "Dot"}}'

Ayrıntılar

Barındırma: Hazır hizmet (bulut), Kendi sunucunda
Kullanılabildiği yerler: Tüm dünya
Resmi SDK'lar: Python, JavaScript/TypeScript, Rust, Go, C#, Java
MCP sunucusu: Yerel sunucu