Popular document database with built-in vector search for RAG.
Category: Memory & Data · Type: Document database + vector search · Website: https://www.mongodb.com
Overview
MongoDB is a widely used document database whose Atlas Vector Search lets teams store operational data and embeddings together, simplifying RAG by keeping documents and their vectors in one place.
Key Features
- Flexible JSON document model
- Atlas Vector Search for embeddings
- Operational data + vectors in one store
- Managed Atlas cloud
Role in the Agentic AI Stack
A general-purpose data store that doubles as a vector database for agent RAG; competes with dedicated stores like Qdrant.
Part of Agentic AI Landscape → Memory & Data