About MongoDB Atlas Vector Search
Atlas Vector Search is MongoDB Atlas’s native vector search capability that stores and queries embeddings alongside operational data, enabling hybrid queries combining vectors, filters, and aggregation pipelines.
Key Features
- Native $vectorSearch operator and ANN/ENN support integrated with MongoDB’s document model and aggregation pipeline.
- Ability to combine vector queries with metadata filters, geo/spatial, graph lookups, and full-text search for hybrid use cases.
- Managed Atlas deployment with Search Nodes and integrations for model/embedding providers and generative AI workflows.
Use Cases & Best For
Developers who want to keep operational data and vectors in one database for RAG, personalization, and hybrid search.
Teams seeking a managed vector search that integrates with existing MongoDB data models, aggregation, and security features.
About Vector Databases
Storage and retrieval for embeddings