Vector Databases

Lightweight open-source embedding database. Simple Python API, runs in-process or as server. Great for prototyping.

Elasticsearch with kNN vector search. Combine full-text and vector search in one system. Mature ops tooling.

Meta's library for efficient similarity search. CPU and GPU optimized. Best for local/embedded vector search.

Serverless vector database built on Lance format. Embedded, no server needed. Great for edge and local apps.

End-to-end vector search engine. Handles embedding generation, storage, and retrieval in one system.

Cloud-native vector database for enterprise AI. Billion-scale vector search with GPU acceleration. Zilliz Cloud managed ...

Serverless PostgreSQL with pgvector support. Auto-scaling, branching, and bottomless storage. Free tier included.

Vector similarity extension for PostgreSQL. Add vector search to existing Postgres without new infrastructure.

Managed vector database for similarity search at scale. Free tier: 1 index, 100K vectors. Low-latency queries.

High-performance vector database written in Rust. Advanced filtering, payload indexing, and distributed deployment.

PostgreSQL + pgvector + Auth + Storage in one platform. Built-in vector search without separate vector DB.

Serverless vector database with pay-per-query pricing. S3-backed storage for cost-efficient large-scale search.

Serverless vector database with pay-per-request pricing. REST API, no connection management needed.

Yahoo's big data serving engine. Combined vector, text, and structured search with real-time indexing at scale.

Open-source vector database with built-in ML models. Hybrid search (vector + keyword). Self-hosted or managed.

Managed Milvus service. Enterprise vector database with auto-scaling, backup, and global deployment.