MongoDB Sees Self-Managed Growth, Expands AI Push Across Atlas and Enterprise

Key Points

• MongoDB’s self-managed Enterprise Advanced business is reaccelerating, with double-digit growth and rising demand from regulated industries, government customers and organizations seeking deployment flexibility. The company views Atlas and self-managed offerings as complementary “two growth engines.”
• MongoDB is expanding feature parity across deployment models, recently making Search and Vector generally available for self-managed customers. Portability, regulatory uncertainty and the ability to run applications across public clouds, on-premises and hybrid environments are key adoption drivers.
• AI remains a major strategic priority, including MCP Server capabilities, agent memory applications, Voyage AI integration and tools such as auto-embedding. Enterprise AI deployments are growing cautiously because of security, privacy, governance and regulatory concerns, while MongoDB continues investing heavily in R&D, sales and developer marketing.

MongoDB NASDAQ: MDB executives said the company is seeing renewed growth in its self-managed Enterprise Advanced, or EA, business alongside continued investment in its Atlas cloud database platform, positioning the two offerings as complementary growth engines rather than competing products.

During a fireside chat, Chief Financial Officer Mike Berry said customer demand for deployment flexibility has increased over the past 12 to 18 months. While Atlas remains a major strategic focus, he said customers in regulated industries, government and other environments are increasingly interested in self-managed deployments because of regulations, data requirements, cloud capacity constraints and economics.

“The run-anywhere strategy is real,” Berry said, referring to MongoDB’s ability to run across public clouds and customer-controlled environments. He added that larger customers commonly use both self-managed MongoDB and Atlas, and that growth among large customers using both products has exceeded the companywide average.

Berry said EA has accelerated in each of the past three quarters and has become a double-digit growth driver, though the company’s disclosed EA annual recurring revenue figure also includes “other” revenue, which is generally associated with OEM transactions. He said MongoDB now views Atlas and self-managed operations as “two growth engines.”

Portability and Feature Parity

Chief Product Officer Ben Cefalo said customers do not necessarily view self-managed deployments as a return to legacy technology. Instead, they value the ability to build an application once and move it among cloud and on-premise environments as needed, including in regions without a cloud provider.

Cefalo said uncertainty around emerging laws, regulations, certifications, governance and privacy requirements has increased the value of portability. He noted that some customer workloads will not move to the cloud for various reasons, and MongoDB has responded by bringing more capabilities to self-managed environments.

The company recently made Search and Vector generally available for self-managed MongoDB after initially developing those capabilities in Atlas, according to Cefalo. He said the release was driven by customer demand for similar functionality across deployment models.

Berry said the self-managed licensing model generally offers higher upfront profitability and may provide higher gross margins over time. However, he emphasized that MongoDB benefits when customers use both its self-managed products and Atlas, as new workloads may be deployed in Atlas and some workloads could eventually migrate to the cloud. He also said the products share much of the same underlying technology, limiting incremental research and development requirements.

AI Product Strategy and Enterprise Adoption

Cefalo outlined several AI-related product priorities, including investments in MongoDB’s MCP Server capabilities, which he described as an interface that enables AI agents to communicate with services. He said the company is also working to bring additional Atlas-developed services to self-managed environments.

MongoDB’s broader goal is to operate as an intelligent data platform, Cefalo said. He described the company’s approach as allowing customers to use services such as Search, Vector, Atlas Data Federation and Online Archive against the same underlying data rather than duplicating information across separate systems. He also cited the company’s Voyage AI acquisition and its auto-embedding capabilities as part of that strategy.

Enterprise adoption of custom AI applications remains in an early phase, according to Cefalo. He said enterprises are broadly running pilots but are moving carefully when applying AI to mission-critical, revenue-generating applications. Security, governance, privacy, GDPR, laws and regulations are among the factors slowing production deployments, particularly in regulated industries.

Cefalo also said MongoDB is being used as a memory layer for AI agents. Because agents commonly use JSON for inputs and outputs, he said MongoDB’s native JSON database architecture makes it a natural place for customers to store that information. The company has also invested in a partnership with LangChain as part of its participation in the agentic AI ecosystem.

Investment, Margins and Go-to-Market Efforts

Berry said MongoDB has expanded operating margins by improving spending discipline while continuing to invest for growth. He said the company conducted a small sales restructuring after determining that some added capacity was not producing sufficient productivity.

For the current fiscal-year guidance discussed during the event, Berry said research and development spending is projected to rise about 30%, while sales and marketing spending is expected to increase in the mid-teens and general and administrative spending by lower single digits. The company expects to continue investing in R&D, sales capacity, AI-native customers and the integration of Voyage AI customers.

He said MongoDB has only begun using AI internally and intends to reinvest efficiencies from automation into growth rather than primarily directing savings to the bottom line. “Growth will always be the number one priority,” Berry said.

On customer acquisition, Berry said MongoDB has reinvested in developer marketing and awareness efforts, including its “Reclaim the Bay” initiative. He said the company’s product-led growth organization has helped convert members of its developer community into customers. More recently, customer additions have been helped by Voyage AI, although Berry said that activity has not yet become a meaningful percentage of revenue.

Berry also said Chief Executive Officer CJ has increased the company’s focus on customers, enterprise growth and operational discipline, including monthly and quarterly operating reviews designed to identify leading indicators and make adjustments during a quarter.

About MongoDB (NASDAQ:MDB)

MongoDB, Inc develops database software and data platform services for organizations building, deploying and operating modern applications. Its flagship technology is a document-oriented database that stores data in flexible, JSON-like documents, helping developers manage varied data structures and support applications that require scalability and rapid development.

The company offers MongoDB Atlas, a fully managed cloud database service available across major cloud providers, as well as MongoDB Enterprise Advanced for organizations that operate databases in private, hybrid or multicloud environments.

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