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MongoDB Atlas Vector Search

Free tier

Build intelligent applications powered by semantic search and generative AI with a native, full-featured vector database.

Free tier available·All audiences·Powered by Voyage AI (Automated Embeddings); any LLM via RAG·API available
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Key strengths

Unified operational and vector data in a single platform — no sync overheadHybrid search combining vector, lexical, geospatial, and metadata filteringAutomated Embeddings powered by Voyage AI — no ML expertise requiredIndependent scaling of vector search via dedicated Search NodesEnterprise-grade security, high availability, and multi-cloud support
Free tier + paid plans
New York, USA
Founded 2007
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MongoDB Atlas Vector Search leverages Lucene-based indexing (HNSW for Approximate Nearest Neighbor and flat indexes for exact search) natively within the Atlas platform, enabling vector queries to be combined with MongoDB's full aggregation pipeline, metadata filters, graph lookups, geospatial queries, and lexical (BM25) search in a single request. Dedicated Search Nodes provide workload isolation, allowing vector query compute to scale independently from the operational database layer. The platform supports Retrieval-Augmented Generation (RAG) patterns, agentic AI systems, and multitenant vector search architectures. Automated Embeddings (Voyage AI integration) handles embedding generation and synchronization directly in the database tier.