MongoDB brings search and vector search to local environments

"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."

"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."

"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."

MongoDB Community Edition and Enterprise Server now include built-in search and vector search for local development and testing, previously available only in the Atlas cloud service. Integration eliminates the need for external search engines or separate vector databases, reducing complexity and operational overhead. Teams can build AI and RAG applications locally using semantic vector embeddings to query unstructured data such as documents, images, video, and audio. Hybrid search combines keyword and vector matching in a single query to improve accuracy and remove ETL pipelines and synchronization issues. Enterprise Server supports secure use of proprietary data for agentic AI solutions while Community Edition enables prototyping.

Read at Techzine Global