Qdrant

Fully-managed serverless vector database for RAG and semantic search.

Fully-managed vector DB built for production RAG and semantic search at scale. Serverless pricing, low-latency reads, and integrations across every major framework, with no infrastructure to provision or operate.

Open-source vector database with built-in vectorisers.

Cloud-native vector DB that can compute embeddings inline — pass raw text in, store vectors out. Strong hybrid (BM25 + vector) search; self-hostable or managed.

Distributed vector database built for billion-scale search.

Cloud-native, Apache-2.0 vector database for similarity search at scale, powering RAG, semantic and multimodal search, and recommendations. Its distributed architecture separates storage and compute and supports many index types (HNSW, IVF, FLAT, DiskANN, SCANN) with quantization and mmap. Created by Zilliz, which offers the managed Zilliz Cloud.

Embedded vector DB. Pip-install, prototype, scale later.

The low-friction starting point — Chroma runs embedded inside your Python process or as a hosted service. Great for prototypes and small-to-medium RAG apps; upgrade to a managed option when you outgrow it.