MongoDB Extends Search and Vector Search Capabilities to Self-Managed Offerings
MongoDB Enables Millions of Developers to Securely Build AI Applications on Any Infrastructure
New York, NY — September 17, 2025 — MongoDB, Inc. (NASDAQ: MDB) today at its developer conference MongoDB.local NYC announced the integration of search and vector search capabilities with MongoDB Community Edition and MongoDB Enterprise Server.
Previously exclusive to the fully managed MongoDB Atlas cloud platform, developers and organizations of all sizes can now access the preview of robust full-text search and vector search capabilities on MongoDB’s local, on-premises, and self-managed offerings—all with the world’s most popular modern database. Starting today, these capabilities are in public preview for development and testing purposes.
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 large language models (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, allowing them to stay focused on building intelligent applications,” Pratt added.
Meeting the Demands of Modern AI Applications
Customers today expect high-performing, personalized, and real-time modern applications. To meet those demands, developers and enterprises alike require comprehensive AI search and retrieval tools integrated into the database where their data is stored.
These native out-of-the-box search and AI-driven capabilities include full-text, semantic retrieval, and hybrid search — delivering highly accurate, intelligent, and context-aware retrieval-augmented generation (RAG) and agentic AI user experiences.
“At MongoDB, we believe in empowering developers everywhere with the tools they need to build next-generation 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.”
Enabling Developers to Build More Powerful Applications
Previously, integrating search capabilities into self-managed MongoDB environments required adding external search engines or vector databases. Managing a fragmented search stack added complexity and risk, increasing operational overhead that could lead to fragile extract, transform, and load (ETL) pipelines, synchronization errors, and higher costs.
This meant developers had to use and manage multiple systems from different vendors just to add search features — which proved complicated, risky, and expensive.
Now, with search and retrieval capabilities directly integrated into MongoDB Community Edition and MongoDB Enterprise Server, developers and organizations can:
- Test and build AI applications locally: Vector search enables semantic information retrieval based on meaning encoded in vector embeddings. This empowers users to manage and build dynamic AI applications that rely on unstructured data like text documents, images, videos, audio files, chat messages, and more—all within their local or on-premises environments.
- Boost accuracy with hybrid search: Combine keyword and vector search to return unified results from a single query for more accurate outcomes. Crucial for reliable agentic solutions and AI applications, developers can easily take advantage of this powerful capability directly through MongoDB’s familiar query framework.
- Power AI agents with long-term memory: Allow data in MongoDB to serve as the long-term memory store for AI agents, enabling precise, context-aware applications ready for real-world situations. With Community Edition, developers can easily prototype RAG systems. Organizations building on Enterprise Server can securely ground AI agents in proprietary data on their own infrastructure.
MongoDB is a unified document database that gives developers the tools they need to build modern applications to handle any use case, all in one place. Today, MongoDB furthers this commitment with the integration of powerful search and retrieval capabilities that will help developers build intelligent AI applications to provide relevant context for agentic systems in their environment of choice.
MongoDB Partners Validate New Search Capabilities in Community Edition
A number of MongoDB partners—including LangChain, a provider of software development frameworks for building LLM-powered applications, and LlamaIndex, an open-source framework for LLM applications—collaborated closely with MongoDB to test search and vector search capabilities 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 iteration of search experiences in MongoDB Community Edition.”
Jerry Liu, CEO of LlamaIndex, added, “Our customers want the highest flexibility to be able to run their search and generative AI-enabled applications, and bringing this functionality to Community unlocks a whole new way to build and test anywhere.”
To learn more, check out the MongoDB blog.
About MongoDB
Headquartered in New York, MongoDB’s mission is to empower innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform was built to power the next generation of applications, and MongoDB is the most widely available, globally distributed database on the market.
With integrated capabilities for operational data, search, real-time analytics, and AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures.
Millions of developers and more than 50,000 customers across industries—including over 75% of the Fortune 100—rely on MongoDB for their most important applications.
To learn more, visit mongodb.com.
