MongoDB, announced at its MongoDB.local NYC developer conference the availability of search and vector search capabilities within MongoDB Community Edition and MongoDB Enterprise Server. Previously offered only through the fully managed MongoDB Atlas cloud platform, these features are now in public preview for development and testing across local, on-premises, and self-managed environments making advanced AI-powered search accessible to a broader range of developers and organizations.
“According to a 2025 IDC survey, more than 74% of organizations plan to use integrated vector databases to store and query vector embeddings within their agentic AI workflows,” said Devin Pratt, Research Director at IDC. “In a fast-moving technological era driven by LLMs and AI applications, developers can’t afford to be slowed down by fragmented systems. Embedding search and vector search directly into the database gives them one less complexity to manage, and allows them to stay focused on building intelligent applications.”
Modern applications demand real-time, personalized, and high-performance experiences, powered by intelligent data retrieval. To address these needs, MongoDB now integrates full-text search, semantic retrieval, and hybrid search directly into its database, enabling developers to deliver highly accurate and context-aware retrieval-augmented generation (RAG) and agentic AI applications.
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“At MongoDB, we believe in empowering developers everywhere with the tools they need to build next-gen applications,” said Benjamin Cefalo, Senior Vice President, Head of Core Products at MongoDB. “By expanding our Search and Vector Search capabilities, we’re giving developers unparalleled flexibility to build in the environment of their choice, with the ultimate customer guarantee that the core database and query capabilities they love in MongoDB Atlas are also freely available in Community. And when they’re ready to bring their applications to market, they can easily migrate to our fully managed MongoDB Atlas platform for seamless scaling, multi-cloud flexibility, and enterprise-grade security.”
Simplifying AI Application Development
In the past, self-managed MongoDB users relied on external search engines or vector databases to add search functionality. This fragmented approach increased costs and operational risks, often leading to fragile ETL pipelines and synchronization issues. By embedding native search and vector search directly into Community Edition and Enterprise Server, MongoDB eliminates these complexities and provides developers with a unified solution to:
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Build and test AI applications locally: Vector search allows semantic retrieval of information from text, images, audio, video, and other unstructured data, enabling developers to create advanced AI-driven applications in on-premises or local setups.
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Enhance precision with hybrid search: Combining keyword and vector search produces unified results from a single query, a critical feature for reliable AI and agentic systems.
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Power AI agents with long-term memory: MongoDB can now serve as a long-term memory store for AI agents. Developers using Community Edition can prototype RAG systems, while enterprises leveraging Enterprise Server can securely ground AI agents in proprietary data on their infrastructure.
With these enhancements, MongoDB reinforces its position as a comprehensive document database built to support modern workloads, delivering the scalability, flexibility, and intelligence required to advance enterprise-grade AI applications.
Partner Ecosystem Supports New Capabilities
MongoDB collaborated with leading AI framework providers, including LangChain and LlamaIndex, to test the new search and vector search features in Community Edition.
“We’re thrilled MongoDB search and vector search are now accessible in the already popular MongoDB Community Edition,” said Harrison Chase, CEO, LangChain. “Now our customers can leverage MongoDB and LangChain in either deployment mode and in their preferred environment to build cutting edge LLM applications.”
“We’re excited about the next interaction of search experiences in MongoDB Community Edition. Our customers want the highest flexibility to be able to run their search and gen AI-enabled applications, and bringing this functionality to Community unlocks a whole new way to build and test anywhere,” said Jerry Liu, CEO, LlamaIndex.