MongoDB.local.NYC 2025: Defining the Ideal Database for the AI Era

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 modernization." 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 on 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.