MongoDB, Inc. Q2 FY2026 earnings call

• Upcoming Investor Day on September 17 in New York City to discuss investments for durable growth and margin expansion. • Strong Q2 results with revenue growth, Atlas accelerating to 29% YOY growth (up from 26% in Q1), and over 5,000 new customers added in the last two quarters. • MongoDB is enterprise-ready, suitable for various use cases including mission-critical and transaction-intensive applications, and has natively included capabilities like search, vector search, embeddings, and stream processing. • Highlighted examples like Deutsche Telekom and Agibank using MongoDB Atlas for their applications. • Mentioned emerging role in AI applications, with many AI-native startups choosing Atlas, though current Q2 growth not materially driven by AI customers. • Modest restructuring in the quarter with less than 2% of employees impacted and ~$5 million in one-time charges excluded from non-GAAP financials.

MongoDB, Inc. generated revenue of $591 million in the second quarter, up 24% year over year and above guidance. Atlas revenue grew 29% year over year, representing 74% of total revenue. Non-GAAP operating income was $87 million with a 15% non-GAAP operating margin. The company ended the quarter with over 59,900 customers, with Atlas having over 58,300 customers at quarter end.

• Raised full-year revenue guidance to $2.34 to $2.36 billion, an increase of $70 million from prior guidance. • Increased operating margin guidance to 14% at the high end, up from 12.5% in prior guidance. • Q3 revenue expected to be in the range of $587 to $592 million. • Non-GAAP income from operations expected to be in the range of $66 to $70 million. • Non-GAAP net income per share expected to be in the range of $0.76 to $0.79 for Q3.

Q: Sanjit Singh with Morgan Stanley asked about the drivers of Atlas's strong sequential dollar adds.

A: Dev Ittycheria said it was due to workloads acquired over the past year moving upmarket, growth in capabilities like search and vector search, and addition of new customers.

Q: Raimo Lenschow with Barclays asked about self-serve acceleration and non-Atlas ARR.

A: Dev Ittycheria discussed data-driven experiments in self-serve, including targeting SQL developers, and Mike Gordon mentioned the impact of multiyear deals on non-Atlas ARR is tied to Q3 performance.

Q: Tyler Radke with Citi asked about AI commentary and migration opportunity.

A: Dev Ittycheria said AI growth in Q2 wasn't material, and discussed app modernization efforts with investment in product and resources for code migration.

Q: Jason Ader with William Blair asked about industry developments and Postgres adoption.

A: Dev Ittycheria talked about OLTP being the strategic high ground for AI and JSON support as a differentiator, and explained Postgres's limitations for scaling as startups grow.

Q: Mike Cikos with Needham asked about Atlas trends and multiyear deals.

A: Mike Gordon discussed Atlas consumption growth consistency, broad-based strength, and multiyear deals not being pull-forwards but good underlying strength in ARR growth.

Q: Alex Zukin with Wolfe Research asked about AI balance and margin.

A: Mike Gordon said revenue growth drives margin expansion, and it's a company-wide effort to invest in growth that drives returns.

Q: Kash Rangan with Goldman Sachs asked about AI go-to-market and enterprise AI.

A: Dev Ittycheria talked about transitioning self-serve customers to direct sales and enterprise AI being early in its journey with low-stakes use cases currently.

Q: Brad Reback with Stifel asked about EA ARR growth.

A: Dev Ittycheria discussed enterprise customers valuing optionality of running workloads on-prem or in the cloud with MongoDB's code base.

Q: Ittai Kidron with Oppenheimer asked about AI go-to-market and multiyear deals.

A: Mike Gordon discussed multiyear deal mix and Dev Ittycheria talked about AI adoption inflection points and agent needs for MongoDB's platform.

Q: Siti Panigrahi with Mizuho asked about AI implementation slowdown.

A: Dev Ittycheria discussed customer hesitations around AI output quality, security, and scalability, and the learning journey for AI adoption.

Q: Brad Sills with Bank of America asked about R&D investments and higher quality workloads.

A: Dev Ittycheria mentioned R&D investments in platform releases and application modernization, and attributed growth to higher quality workloads from upmarket focus.

Q: Rishi Jaluria with RBC asked about MongoDB's role in multi-agentic future.

A: Dev Ittycheria explained MongoDB's JSON database, search/vector search capabilities, and memory support as suited for agent needs in the future.