Qdrant

Rust로 구현한 오픈소스 벡터 DB. 매니지드·엔터프라이즈 제공, payload 필터·하이브리드·양자화로 메모리와 처리량 최적화.

적합한 경우

Open-source, self-hostable vector DB with strong performance and expressive filters—solid pick for small/medium RAG. Cloud offering available too.

덜 맞는 경우

Teams with zero ops capacity, or trivial vector needs where pgvector/SQLite is enough.

비교 시 참고

Vs Weaviate / Milvus / Pinecone: Qdrant is praised for Rust-based speed and filter expressiveness; multi-tenant and cloud maturity keep improving.

점검 체크리스트

Decide OSS vs Qdrant Cloud boundary
Design collection + payload indexes to avoid full scans
Benchmark recall@k and P95 latency with real data
Plan backups/snapshots and replication

검색 Q&A

What RAG scale fits Qdrant?

From hundreds of thousands to hundreds of millions of vectors. For cross-node writes and strict multi-tenant isolation, consider Qdrant Cloud or benchmark a self-managed cluster first.

활용 상황

위 소개로 이 도구가 적합한지 가늠할 수 있습니다. 비슷한 도구가 많다면 사용 빈도, 예산, 데이터 프라이버시를 먼저 정리하고 고르세요.