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MongoDB | Blog

10 Years of MongoDB Atlas: Built for what’s Next Build Trust in Agentic AI: From POC to Production Production-Ready Agents Need A Production-Ready Data Platform Agentic Supplier Management with MongoDB Atlas, Voyage AI, and Multi-Modal Search Fighting Tool Sprawl: The Case for AI Tool Registries AI Is Changing What Customers Need From a Database. MongoDB 8.3 Is Built for It New Research Reveals Overcoming Legacy Tech Issues Key to AI Success MongoDB Predictive Auto-Scaling: An Experiment Introducing MongoDB Agent Skills and Plugins for Coding Agents Enhance Your In-IDE Data Browsing Experience With MongoDB Observability and OpenTelemetry: Introducing MongoDB Atlas Log Integration Towards Model-based Verification of a Key-Value Storage Engine Inside MongoDB Dublin: The Heart of Our International Growth Innovating with MongoDB | Customer Successes, February 2026 Building a Movie Recommendation Engine with Hugging Face and Voyage AI Edge AI Made Easy: MongoDB and ObjectBox Data Synchronization MongoDB.local San Francisco 2026: Ship Production AI, Faster Vision RAG: Enabling Search on Any Documents That’s a Wrap! MongoDB’s 2025 in Review & 2026 Predictions Token-count-based Batching: Faster, Cheaper Embedding Inference for Queries MongoDB Announces Leadership Transition Cars24 Improves Search For 300 Million Users With MongoDB Atlas The Cost of Not Knowing MongoDB, Part 3: appV6R0 to appV6R4 The 10 Skills I Was Missing as a MongoDB User Innovating with MongoDB | Customer Successes, October 2025 Smarter AI Search, Powered by MongoDB Atlas and Pureinsights Charting a New Course for SaaS Security: Why MongoDB Helped Build the SSCF Top Considerations When Choosing a Hybrid Search Solution Endian Communication Systems and Information Exchange in Bytes MongoDB SQL Interface: Now Available for Enterprise Advanced From Niche NoSQL to Enterprise Powerhouse: The Story of MongoDB's Evolution Carrying Complexity, Delivering Agility MongoDB is a Glassdoor Best-Led Company of 2025 Build AI Agents Worth Keeping: The Canvas Framework Simplify AI-Driven Data Connectivity With MongoDB and MCP Toolbox MongoDB Community Edition to Atlas: A Migration Masterclass With BharatPE Modernizing Core Insurance Systems: Breaking the Batch Bottleneck MongoDB.local NYC 2025:定义 AI 时代的理想数据库 MongoDB.local NYC 2025: Definiendo la base de datos ideal para la era de la IA MongoDB.local NYC 2025 : définir la base de données idéale à l'ère de l'IA MongoDB.local NYC 2025: Definindo o Banco de Dados Ideal para a Era da IA MongoDB.local NYC 2025: AI 시대를 위한 이상적인 데이터베이스 정의 MongoDB.local NYC 2025: Definition der idealen Datenbank für das KI-Zeitalter MongoDB.local NYC 2025: Definire il database ideale per l'era dell'AI Hommage à l’excellence : MongoDB Global Partner Awards 2025 Wir feiern Spitzenleistungen: MongoDB Global Partner Awards 2025 Celebrating Excellence: MongoDB Global Partner Awards 2025 庆祝卓越:MongoDB 全球合作伙伴奖 2025 Celebrando la Excelencia: Premios Globales de Emparejar de MongoDB 2025 Começando a destacar a excelência: MongoDB GlobalPartner Services 2025 Celebrare l'eccellenza: MongoDB Global Partner Awards 2025 우수성을 기념하기: 2025년 MongoDB 글로벌 파트너 어워드 The Future of AI Software Development is Agentic MongoDB Queryable Encryption Expands Search Power Supercharge Self-Managed Apps With Search and Vector Search Capabilities Potencie las aplicaciones autogestionadas con capacidades de búsqueda y búsqueda vectorial
MongoDB.local NYC 2025: Defining the Ideal Database for the AI Era
Dev Ittycheria, President and CEO, MongoDB · 2025-09-18 · via MongoDB | Blog

Yesterday, we welcomed thousands of developers and executives to MongoDB.local NYC, the latest stop in our global .local series. Over the past year, we’ve connected with tens of thousands of partners and customers in 20 cities worldwide. But it’s especially meaningful to be in New York—where MongoDB was founded and where we are still headquartered.

During the event, we introduced new capabilities that advance MongoDB’s position as the world’s leading modern database. With MongoDB 8.2, our most feature-rich and performant release yet, we are raising the bar for what developers can achieve. We also shared more about our Voyage AI embedding models and rerankers, which bring state-of-the-art accuracy and efficiency to building trustworthy, reliable AI applications. And with Search and Vector Search now in public preview for both MongoDB Community Edition and Enterprise Server, we are putting powerful retrieval capabilities directly into customers’ environments—wherever they prefer to run.

I am particularly excited about the launch of the MongoDB Application Modernization Platform, or AMP. Enterprises everywhere are grappling with the massive costs of legacy systems that cannot support the demands of AI. AMP is not a simple “lift-and-shift.” It is a repeatable, end-to-end platform that combines AI-powered tooling, proven techniques, and specialized talent to reinvent critical business systems while minimizing cost and risk. Early results are impressive: enterprises moving from old systems to MongoDB are doing so two to three times faster, and tasks like code rewriting are accelerating by an order of magnitude.

Becoming the world’s most popular modern database

When I reflect on MongoDB’s journey, I’m struck by how far we’ve come. When I joined just over a decade ago, we had only a few thousand customers. Today, MongoDB serves nearly 60,000 organizations across every industry and vertical, including more than 70% of the Fortune 500 and cutting-edge AI-native startups.

Yet the reason behind our growth remains the same. Relational databases built in the 1970s were never designed for the scale and complexity of modern applications. They were rigid, hard to scale, and slow to adapt. Our founders, who had lived those limitations first-hand while building DoubleClick, set out to create something better: a database model designed for the realities of the modern world. The document model was born.

Based in JSON, the document model is intuitive, flexible, and powerful. It allows developers to represent complex, interdependent, and constantly changing data in a natural way. And, as we enter the era of AI, those same qualities—adaptability, scalability, and security—are more critical than ever. The database a company chooses will be one of the most strategic decisions determining the success of its AI initiatives.

Generative AI applications have already begun delivering productivity gains, writing code, drafting documents, and answering questions. But the real transformation lies ahead with agentic AI—applications that perceive, decide, and act. These intelligent agents don’t just follow workflows; they pursue outcomes, reasoning about the best steps to achieve them. And in that loop, the database is indispensable. It provides the memory that allows agents to perceive context, the facts that allow them to decide intelligently, and the state that will enable them to act coherently.

This is why a company’s data is its most valuable asset. Large language models (LLMs) may generate responses, but it is the database that provides continuity, collaboration, and true intelligence. The future of AI is not only about reasoning—it is about context, memory, and the power of your data.

The ideal database for transformative AI

So what does the ideal database for agentic AI look like? It must reflect today’s complexity and tomorrow’s change. It must speak the language of AI, which is increasingly JSON. It must integrate advanced retrieval across raw data, metadata, and embeddings—not just exact matching but meaning and intent. It must bridge private data and LLMs with the highest-quality embeddings and rerankers. And it must deliver the performance, scalability, and security required to power mission-critical applications at a global scale.

This is precisely what MongoDB delivers. We don’t simply check the boxes on this list—we define them.

We’re only just getting started

That’s why I am so optimistic about our future. The energy and creativity we see at every MongoDB.local event remind me of the passion that has always fueled this company. As our customers continue to innovate, I know MongoDB is in the perfect position to help them succeed in the AI era.

We can’t wait to see what you build next.

To see more announcements and for the latest product updates, visit our What’s New page. And head to the MongoDB.local hub to see where we’ll be next.