MongoDB, Inc. Q3 FY2026 earnings call

• Atlas performance was strong with 30% year-over-year growth, accelerating from previous quarters. Total revenue exceeded guidance due to Atlas strength.
• Delivered non-GAAP operating income of $123.1 million with a 20% non-GAAP operating margin. Customer count exceeded 62,500, with 2,600 new customers added in the quarter.
• Highlighted examples of customer adoption, like a global insurance provider using MongoDB Atlas for mission-critical systems, leading to scalability and innovation.
• Emphasized MongoDB's position in the AI era, with AI-native companies using MongoDB for intelligent applications and large enterprises exploring AI agents built on MongoDB.

Atlas revenue saw 30% year-over-year growth in the third quarter, representing 75% of total revenue. Non-Atlas revenue had an 8% year-over-year growth in ARR. Total revenue for the quarter was $628.3 million, up 19% year-over-year. Atlas consumption growth was consistent, driving revenue acceleration, and non-Atlas revenue outperformed expectations with higher-than-expected multiyear revenue.

• Fourth quarter revenue expected to be $665 million to $670 million (21%-22% year-over-year growth). Non-GAAP income from operations expected $139 million to $143 million (~21% operating margin). Non-GAAP net income per share $1.44 to $1.48.
• Full fiscal year 2026 revenue expected $2.434 billion to $2.439 billion (21%-22% growth). Non-GAAP income from operations $436.4 million to $440.4 million (~18% operating margin). Non-GAAP net income per share $4.76 to $4.80.
• Atlas expected to have ~27% revenue growth in Q4 fiscal 2026. Non-Atlas business expected upper single-digit percent growth year-over-year in Q4. Free cash flow conversion expected over 100% for fiscal 2026.

• Risks related to results of operations and financial conditions that could cause actual results to differ materially from expectations, as outlined in the quarterly report on Form 10-Q for the quarter ended July 31, 2025.

Q: Sanjit Singh from Morgan Stanley asked about quick wins and long-term changes for MongoDB in the AI era.

A: Chirantan Desai mentioned embedding models and vector database as low-hanging fruit, and MongoDB's role in AI agents transforming businesses.

Q: Matthew Martino from Goldman Sachs asked about customer themes.

A: Chirantan Desai talked about modernization efforts, AI experimentation, and AI-native companies switching to MongoDB due to scaling issues.

Q: Karl Keirstead from UBS asked about core strength driving and AI tailwind.

A: Chirantan Desai said core strength is from modernization of unstructured/semi-structured data workloads, and AI could drive more modernization.

Q: Raimo Lenschow from Barclays asked about developer engagement and non-Atlas guidance.

A: Chirantan Desai and Dev Ittycheria discussed reclaiming the Bay Area and marketing efforts, while Mike Berry said non-Atlas next year likely in low single digits growth.

Q: Brad Reback from Stifel asked about new customer strength in Atlas.

A: Chirantan Desai and Dev Ittycheria mentioned engineering improvements and self-serve team reducing friction for new customers.

Q: Aleksandr Zukin from Wolfe Research asked about growth inflection and AI synergy.

A: Chirantan Desai discussed Fortune 500 penetration and AI-native company adoption, with examples of landing with Voyage AI embeddings.

Q: Ryan MacWilliams from Wells Fargo asked about enterprise product velocity.

A: Dev Ittycheria and Chirantan Desai talked about prototyping and iteration in enterprise applications, with recognition of differences between prototypes and production-grade systems.