Developers can now use search and vector search functionality in MongoDB Community Edition and Enterprise Server. These capabilities were previously only available in the Atlas cloud service.
During the MongoDB.local NYC conference, MongoDB announced that search and vector search will be available for local installations. The previews are intended for development and testing. Until now, developers and organizations that wanted to use these features had to rely on the fully managed MongoDB Atlas cloud service.
End of fragmented stacks
Integrating search capabilities into self-managed MongoDB environments previously required external search engines or vector databases. This led to complexity and operational overhead. Teams had to manage different systems from different vendors to add search capabilities.
With the new capabilities, teams can build AI applications locally. Vector search enables semantic search based on vector embeddings. This enables users to develop dynamic AI applications that interact with unstructured data, including documents, images, videos, and audio.
Hybrid search for better results
Direct integration into the database eliminates the need for Extract, Transform, and Load pipelines between different systems. Synchronization errors and higher costs are now a thing of the past.
The new functionality combines keyword and vector search in a single query. This hybrid approach delivers more accurate search results. According to MongoDB, this is crucial for reliable operation of agentic AI solutions.
AI agents can use MongoDB data as long-term memory. This enables context-aware applications that are ready for practical use. With Community Edition, developers can easily prototype RAG systems. Enterprise Server users can securely base AI agents on proprietary data within their own infrastructure.