MongoDB, Inc. (MDB) Earnings

Management highlights

### Overall Financial Performance - Generated total Q1 revenue of $688 million, up 25% year-over-year, accelerating from 22% growth in the year-ago quarter and beating the high end of prior guidance - Delivered non-GAAP operating margin of 18%, up from 16% year-over-year, also exceeding guidance; achieved the second consecutive quarter of GAAP profitability - Ended the quarter with 67,700 total customers, adding 2,500 customers sequentially; total customers with at least $100,000 in ARR reached 2,895, growing 16% year-over-year, with revenue growth from this cohort outpacing total company growth - 45% of Atlas customers with ≥$100k ARR now leverage two or more platform features, up from 37% year-over-year, driven largely by vector and text search adoption for AI use cases - Operating cash flow reached $202 million (up from $110 million YoY) and free cash flow reached $198 million (up from $106 million YoY), driven by strong operating profit and seasonal cash collection strength ### AI Opportunity and Product Momentum - AI adoption is accelerating across the customer base: MCP server usage is growing significantly, Voyage AI embedding customers more than doubled quarter-over-quarter, and vector search adoption is outpacing overall company growth - The AI opportunity spans three high-potential segments: frontier AI labs, AI-native startups, and existing enterprise customers building AI applications on their existing MongoDB data; management notes MongoDB is purpose-built for agentic AI workloads due to five core strengths: flexible JSON-based native schema suited for prompt-driven development and LLM output, high-performance transactional architecture built for continuous agent read/write activity, best-in-class integrated vector search/embeddings for accurate retrieval that reduces token costs, multi-environment support across all major public clouds, on-premise, and hybrid deployments, and deep native integrations with popular AI development tools including LangChain - MongoDB 8.3, released in Q1, delivers up to 45% more reads, 35% more writes, and 15% more ACID transactions than version 8.0 with no code changes required; automated Voyage AI embeddings entered public preview, cutting development time for semantic search from weeks to minutes ### Organizational Updates - Added several new C-suite leaders to support growth: Ben Cefalo (longtime MongoDB leader) as Chief Product Officer for Core Products (Atlas and Enterprise Advance), Pablo Stern-Plaza as Chief Product Officer for AI and Emerging Products (focused on AI portfolio and strategic relationships with AI customers), Erika Volini as Chief Customer Officer (with experience scaling enterprise go-to-market at ServiceNow), and Ryan McBain as Chief Revenue Officer (with cloud platform scaling experience from Confluent) - Acquired Clarity Business Solutions to accelerate growth in the U.S. federal vertical; Clarity brings deep domain expertise and high-level security clearances for classified government workloads, and contributes ~$10 million in annual services revenue at roughly break-even profitability - MongoDB will host an Investor Day in New York City on September 29, 2026

Guidance

- For Q2 fiscal 27: Expects total revenue of $729 million to $734 million, representing 23% to 24% year-over-year growth. Expects Atlas year-over-year revenue growth of approximately 26%, and EA and other revenue growth of approximately 20% driven by the timing of large closed multi-year existing customer deals. Expects non-GAAP operating income of $152 million to $156 million (for ~21% non-GAAP operating margin at the high end of guidance), and non-GAAP net income per diluted share of $1.58 to $1.61. - For full fiscal 27: Management raised the full-year total revenue growth guidance to 19% to 20% (from the prior lower range), with total revenue expected to reach $2.92 billion to $2.96 billion. Atlas full-year growth guidance was raised 200 basis points to a range of 23% to 25% year-over-year. EA and other full-year growth guidance was raised to mid-single-digit year-over-year growth, with EA revenue expected to be approximately flat year-over-year in the second half of fiscal 27 due to tough comparisons from a very strong second half of fiscal 26. - Full fiscal 27 non-GAAP operating margin is expected to expand 100 to 150 basis points year-over-year, reaching approximately 20% at the high end of guidance, resulting in targeted Rule of 40 performance at the high end of the outlook. Full-year non-GAAP net income per diluted share is expected to be $5.95 to $6.14, based on an expected 20% non-GAAP tax rate. - Management notes that Atlas has become more predictable as it has scaled, with lower sensitivity to individual customer consumption swings, and expects only modest inter-quarter variability in Q2 results; full-year Atlas guidance has more room for variability due to its consumption-based model.

Segment performance

1. Atlas: Revenue grew 29.4% year-over-year, adding a record $117 million in year-over-year growth, reaching a $2 billion annual run rate. This marks the fourth consecutive quarter of at least 29% year-over-year growth. Atlas contributed approximately 75% of total Q1 revenue, up from 72% in the year-ago quarter. End-of-quarter Atlas customer count reached 66,400, up from 55,800 year-over-year. Total company net ARR expansion rate was 121% for the quarter, up from 119% a year ago, driven largely by Atlas momentum. 2. EA and Other (formerly Non-Atlas): Revenue grew 13% year-over-year, with ARR (normalized for duration impacts) growing approximately 11% year-over-year. EA and Other contributed approximately 25% of total Q1 revenue. Growth was driven by existing customers across finance and technology verticals expanding on-premise footprints for traditional and AI applications.

Risks & headwinds

- Forward-looking statements (including AI growth expectations, consumption forecasts, and guidance) are subject to material risks and uncertainties that could cause actual results to differ materially from expectations, with key risks outlined in MongoDB's most recent Form 10-K filing with the SEC. - EA revenue forecasting is inherently uncertain due to variability in the timing of large multi-year EA deals; management only includes closed or high-probability deals in guidance to avoid negative surprises, which can create variability in full-year results. - Agentic AI workload scaling is still in early stages, with multiple unresolved requirements around security, governance, and observability that need to be addressed for widespread large-scale production adoption.

Analyst Q&A

• Q: With agentic AI workloads now moving from proof of concept to production, when will this start to meaningfully move the needle on MongoDB consumption? /

  A: Management confirms it is still early days for large-scale production agentic AI, as many requirements around security, governance, and observability are still being addressed for customer-facing workloads at scale. However, MongoDB has already built all required capabilities into a single integrated platform, and management is seeing very encouraging early demand, with large Fortune 25 enterprises already preparing to roll out production agentic workloads using MongoDB as an operational and memory layer. Management states MongoDB is fully ready to scale as adoption grows.

• Q: How should we think about AI-native customer contribution to Atlas growth, and what use cases drive MongoDB adoption for these customers? /

  A: AI-native companies are increasingly choosing MongoDB as an all-in-one data platform, because fragmented legacy data stacks (with separate tools for operational data and search) create performance bottlenecks and outages that impede rapid scaling. MongoDB's integrated platform, which combines operational data, search, and vector search in one deployment, solves these pain points, and management is seeing strong early traction from fast-growing AI-native customers. While AI-native contribution is growing, the majority of MongoDB's current growth still comes from core enterprise workloads, which are also being prepared for future AI integration.

• Q: What is the catalyst for the Clarity Business Solutions acquisition to expand the U.S. federal vertical? /

  A: MongoDB sees massive untapped opportunity in the U.S. federal market, which has high demand for unstructured data storage and retrieval that MongoDB is well suited to address. The company is on track to receive FedRAMP High certification for Atlas in fiscal 27, and the acquisition of Clarity brings in-house the deep domain expertise and high-level security clearances required to serve classified intelligence and defense workloads that Clarity already supported as a long-time MongoDB partner. Currently the federal business is a small portion of total revenue, but management expects it to grow meaningfully going forward.

• Q: Multiple large blockbuster multi-year deals were announced last quarter; did these ramp in Q1, or is their impact still ahead? /

  A: The deals are multi-year agreements that include a mix of Atlas and EA components, so the majority of the revenue from these deals will be recognized over the term of the agreements, with most future Atlas revenue tied to future customer consumption growth. The portion of the deals that was expected to be recognized in Q1 was already reflected in the Q1 results reported this quarter, and the long-term commitments from these deals support healthy future revenue visibility.