MongoDB Sees AI, Modernization and Self-Managed Demand Fueling Growth

Key Points

• AI and modernization are driving demand for MongoDB’s database platform, with large enterprises increasingly evaluating it for AI architectures, new applications and data-environment upgrades.
• Atlas growth is being supported by enterprise expansion, cross-selling products such as Vector Search and embedding capabilities, and early adoption among AI-native companies. MongoDB also added 2,900 net new customers in the second quarter.
• Self-managed demand is accelerating: Enterprise Advanced grew 36%, prompting MongoDB to raise its full-year growth guidance to 11%. Customers are seeking self-managed deployments because of cloud capacity, cost, data-sovereignty and in-house AI infrastructure considerations.

MongoDB NASDAQ: MDB executives said customer demand for its database platform is being supported by enterprise modernization efforts, AI-related workloads and growing interest in self-managed deployments, while the company works to raise awareness among senior decision-makers.

CJ Desai, MongoDB’s president and CEO, said that after nearly a year in the role and roughly 10 to 12 customer meetings per week, he has found that customers view MongoDB as a modern database capable of supporting large-scale workloads. He said one North American Fortune 100 company had made MongoDB the default standard for new applications unless another technology is justified.

Desai said the company sees a meaningful modernization opportunity as large enterprises prepare their data environments for AI. However, he said MongoDB’s awareness among C-suite executives has historically been limited, even as developers have adopted the platform. He said senior technology leaders are increasingly making top-down decisions about AI architectures and data platforms.

“Sales cycles, when you go top-down, tend to be always long,” Desai said. “But it is early, but it’s working.” He cited discussions with telecommunications, retail and financial-services companies around standardizing on MongoDB and deploying new workloads, including AI applications.

Atlas Growth and AI Workloads

Mike Berry, MongoDB’s chief financial officer, said Atlas growth has been driven primarily by the company’s increased focus on large enterprises, expansion within existing customer accounts and cross-selling products such as Vector Search and embedding capabilities. He said nearly half of MongoDB’s large customers use multiple products, though the revenue contribution from those products remains lower than their adoption rate.

Berry also attributed the durability of Atlas growth to platform reliability and performance, which he said have helped limit customer churn and contraction. He said the company has not seen a major change in the types of workloads it is winning compared with prior periods.

Executives characterized AI demand as early but promising across AI-native companies, frontier labs and large enterprises. Desai cited ElevenLabs as an example of an AI-focused customer that moved to MongoDB after encountering scaling issues with another database service. He said the company benefited from having search and vector search integrated with its operational data layer, reducing the need to move data between systems.

Desai said MongoDB added 2,900 net new customers in the second quarter and expects some of those customers to become more meaningful Atlas users over time. He also said Voyage AI, which provides embedding models, is attracting customers through coding agents such as Claude Code and Codex.

Developer Discovery and Memory Use Cases

Ben Cefalo, MongoDB’s chief product officer, said the company has improved its Model Context Protocol, or MCP, server to reduce friction from sign-up and cluster provisioning through usage. Unlike certain database MCP offerings that provide data access alone, Berry said MongoDB’s MCP can also allow coding agents to provision clusters.

Desai said early data following the launch of managed MCP capabilities on Aug. 13 was encouraging. The company intends to provide additional information at its Investor Day if it accumulates enough data points, he said.

MongoDB is also seeing an emerging opportunity for its platform to serve as a memory layer for AI applications. Desai said a frontier lab is using MongoDB for both short-term and long-term conversational memory, and that an insurance company expressed interest in testing a similar use case after learning about the deployment.

Self-Managed Demand and Modernization

Desai said Enterprise Advanced, MongoDB’s self-managed offering, grew 36% across industries and that the company raised its full-year growth guidance for the product to 11%, compared with 7% in each of the prior two years. He attributed rising self-managed demand to public-cloud capacity constraints, cost considerations for certain workloads, data-sovereignty needs and customer interest in running AI infrastructure in-house.

Berry said self-managed annual recurring revenue had grown more than 10% for three consecutive quarters, compared with low-single-digit growth several years ago. He said the company views Atlas and Enterprise Advanced as two durable growth drivers rather than competing products.

“More Mongo, either Atlas or self-managed, we do not see it cannibalizing Atlas,” Berry said. He added that customers using Enterprise Advanced often also use Atlas, and that Atlas consumption growth among that cohort exceeds the company-wide level.

On modernization, Desai said MongoDB is investing in product capabilities that use AI to reduce migration timelines. The company is working with more than 10 customers during the current fiscal year, aiming to compress modernization projects that may have taken 18 to 24 weeks into four to eight weeks, including database and application-layer work.

Berry said the company is continuing to invest primarily in engineering, along with quota-carrying sales representatives, AI-native customer coverage, marketing awareness and partner capabilities. He said those investments are being made within MongoDB’s existing margin framework.

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.

This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to contact@marketbeat.com.