MongoDB, Inc. (MDB) Q2 2026 Earnings Call Transcript

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Overview

The earnings call summary highlights strong financial performance, with revenue growth exceeding expectations and positive guidance. The increase in the share repurchase program and optimistic outlook for operating margins further support a positive sentiment. The Q&A section reveals confidence in the self-service channel and AI integration, though some details were deferred. Overall, the combination of strong results, strategic initiatives, and shareholder returns suggests a positive stock price movement.

Key Financial Performance

Revenue $591 million, up 24% year-over-year. The increase was driven by strong Atlas revenue growth and broad-based strength, especially in larger customers in the U.S.

Atlas Revenue Grew 29% year-over-year, representing 74% of total revenue. The growth was attributed to a strong start to consumption in May and broad-based strength, particularly among larger customers.

Non-Atlas ARR Grew 7% year-over-year. The growth was supported by success in selling incremental workloads into the existing EA customer base and more multiyear deals than expected.

Customer Base Increased by approximately 2,800 sequentially to 59,900, up from over 50,700 in the year-ago period. Growth was driven primarily by Atlas, which had over 58,300 customers at the end of the quarter.

Gross Margin 74%, down from 75% in the year-ago period. The decline was primarily due to Atlas growing as a percentage of the overall business.

Operating Income $87 million for a 15% non-GAAP operating margin, up from 11% in the year-ago period. The improvement was driven by revenue outperformance and disciplined spending.

Net Income $87 million or $1 per share, compared to $59 million or $0.70 per share in the year-ago period. The increase was due to strong operating profit and higher cash collections.

Operating Cash Flow $72 million, compared to negative $1 million in the year-ago period. The improvement was driven by strong operating profit and higher cash collections.

Free Cash Flow $70 million, compared to negative $4 million in the year-ago period. The improvement was driven by strong operating profit and higher cash collections.

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Operating Highlights

Atlas Revenue: Atlas revenue grew 29% year-over-year, representing 74% of total revenue. The platform is being increasingly adopted for AI applications, with notable use cases in autonomous driving platforms and enterprise-grade deployments.

AI Applications: MongoDB is emerging as a standard for AI applications, with startups and enterprises adopting Atlas for its scalability, flexibility, and performance. Examples include powering autonomous driving platforms and semantic search for AI-native platforms.

New Capabilities: MongoDB has integrated features like vector search, embeddings, and stream processing, making it a comprehensive solution for developers.

Customer Growth: The company added over 5,000 customers in the last two quarters, bringing the total to 59,900 customers. This includes 2,800 new customers in Q2, with 300 from the Voyage AI acquisition.

Enterprise Adoption: Over 70% of the Fortune 500 and major global companies in banking, healthcare, and manufacturing are MongoDB customers. Notable examples include Deutsche Telekom and a leading electric vehicle company.

Revenue Growth: Total revenue reached $591 million, up 24% year-over-year, exceeding guidance. Non-GAAP operating income was $87 million, with a 15% operating margin.

Operational Efficiency: The company undertook a modest restructuring, impacting less than 2% of employees, to reallocate resources to higher ROI opportunities and improve efficiency.

AI Focus: MongoDB is investing in AI capabilities, positioning itself as a key component of the AI infrastructure stack. This includes supporting AI-native startups and enterprise AI applications.

Market Positioning: MongoDB is focusing on durable growth and margin expansion, with a strong emphasis on R&D and developer awareness.

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Risk or Challenges

Regulatory Risks: The company acknowledges that forward-looking statements are subject to a variety of risks and uncertainties, including regulatory hurdles that could impact operations and financial conditions.

Economic Uncertainty: The company highlights economic uncertainties as a factor that could affect its financial performance and strategic objectives.

Atlas Consumption Growth: While Atlas consumption growth was strong, the company notes that it is relatively consistent with last year's growth rates, indicating potential challenges in accelerating growth further.

Non-Atlas Revenue Decline: The company expects a low 20% year-over-year percentage decline in the non-Atlas business for Q3, which could impact overall revenue and profitability.

Customer Base Shift: The company has reallocated go-to-market resources from mid-market to enterprise channels, which has led to a decline in direct sales customers, potentially impacting customer acquisition dynamics.

Multiyear Revenue Headwinds: The company faces a $40 million headwind from multiyear license revenue for fiscal '26, which could affect financial performance.

Operating Margin Pressure: The company expects operating margin to be lower in Q3 due to a sequential decline in high-margin non-Atlas revenue and increased R&D and marketing expenses.

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Guidance & Outlook

Revenue Expectations: MongoDB raised its full-year revenue guidance to a range of $2.34 billion to $2.36 billion, reflecting a $70 million increase from prior guidance. This includes mid-20s percentage growth for Atlas in the second half of the year.

Operating Margin Projections: The company increased its operating margin guidance to 14% at the high end, up from 12.5% in prior guidance, driven by strong Q2 performance and a disciplined approach to investing for growth.

Atlas Growth Expectations: Atlas revenue is expected to grow in the mid-20s percentage range in the second half of fiscal year 2026, with continued strong consumption trends and broad-based strength, especially among larger U.S. customers.

Non-Atlas Revenue Trends: Non-Atlas subscription revenue is now expected to decline in the mid-single digits for the year, an improvement from the prior expectation of a high single-digit decline. Non-Atlas ARR is expected to continue growing year-over-year.

Q3 Revenue Guidance: For the third quarter, revenue is expected to be in the range of $587 million to $592 million, with a sequential decline in non-Atlas revenue due to prior strong multiyear outperformance.

AI and Strategic Investments: MongoDB is making incremental investments in growth areas, particularly in AI and R&D, while maintaining a focus on efficiency and profitability.

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Shareholder Return Plan

share repurchase: During the quarter, we spent $200 million to repurchase approximately 930,000 shares which was under our previously announced $1 billion total share repurchase authorization.

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Key Q&A

Q:What were the drivers of the strong sequential dollar adds in Q2 for Atlas?

A:The strong sequential dollar adds in Q2 were driven by workloads acquired over the past year, particularly from moving upmarket, which are growing faster and becoming larger than previous workloads. Additionally, there was an uptick in capabilities like search and vector search, and a significant number of new customers were acquired, including self-serve customers.

Q:What is the current state of the sales force and go-to-market strategy?

A:The sales force is focused on moving upmarket, targeting sophisticated enterprise customers globally, while the self-serve channel serves the SMB market. The strategy has shown effectiveness in growing wallet share in larger accounts and serving the SMB market without abandoning it.

Q:How has the self-service channel performed despite the move upmarket?

A:The self-service channel has accelerated due to data-driven experiments, targeting SQL developers unfamiliar with MongoDB, and initiatives like office hours to educate developers. These efforts have shown good results, and the team feels confident about the self-serve strategy.

Q:What is the outlook for the non-Atlas or EA part of the business?

A:The outlook for the non-Atlas or EA part of the business depends on Q3 performance this year. Management refrained from providing specific details about next year, emphasizing that it depends on how Q3 unfolds.

Q:How much of the Atlas growth is attributed to AI-related use cases?

A:While MongoDB is adding thousands of AI-native customers, the growth in Q2 was primarily driven by the core business and core customer base. AI-related use cases were not a material driver of growth this quarter.

Q:What is the progress on the migration opportunity and app modernization?

A:MongoDB is investing in app modernization, bringing in new leaders and leveraging AI to build tooling for automation in code analysis and refactoring. While this is a long-term growth driver, more details will be shared at the Investor Day in September.

Q:What is MongoDB's response to industry developments like Lakebase from Databricks and DocumentDB in the Linux Foundation?

A:MongoDB believes OLTP is the strategic high ground for AI and emphasizes its architectural advantages, such as JSON support and integrated search and vector search. Regarding DocumentDB, MongoDB sees it as a sign that real JSON is increasingly important, and hyperscalers are investing less in clones and bolt-ons.

Q:Why is Postgres adoption common among AI startups despite its disadvantages?

A:Many startup founders choose Postgres because they are familiar with it. However, as startups scale, they encounter performance and scalability issues, leading them to switch to MongoDB. MongoDB is investing in developer education and outreach to the startup community to address this.

Q:What were the key drivers of Atlas consumption growth in Q2?

A:Atlas consumption growth in Q2 was driven by broad-based strength across geographies and segments, with notable strength among larger U.S. customers. Workloads from larger customers are growing for longer and expanding more than in the past.

Q:What contributed to the outperformance in multiyear deals this quarter?

A:The outperformance in multiyear deals was due to good underlying strength in ARR growth and greater-than-expected multiyear deals across a broad subset of customers. There were no pull-forwards or large multiyear deals.

Q:What is the differentiation of MongoDB's platform for AI use cases?

A:MongoDB's platform is differentiated by its JSON database, integrated search and vector search, and embedded Voyage models for auto embeddings. These features make it well-suited for handling complex, evolving data structures and hybrid search and retrieval.

Q:What is the current state of AI adoption among enterprises?

A:AI adoption among enterprises is still in its early stages, with most investments focused on end-user productivity and low-stakes use cases. Enterprises are cautious about deploying AI due to concerns about output quality, security, and scalability.

Q:What is MongoDB's strategy for targeting the AI opportunity?

A:MongoDB is focusing on self-serve for early-stage AI customers and transitioning them to a high-touch model as they scale. For enterprises, MongoDB is engaging with customers to support their early AI adoption and positioning itself for long-term growth.

Q:What are the key R&D investments MongoDB is making?

A:MongoDB is investing in platform performance (e.g., 8.0 and 8.1 releases), expanding platform capabilities, and building tooling for app modernization. More details will be shared at the Investor Day in September.

Q:What is the outlook for EA ARR growth?

A:EA ARR growth is driven by large enterprises using a mix of on-premise and cloud deployments. Customers value the flexibility of MongoDB's platform to move between on-premise and cloud environments.

Q:Review of Unclear Management Responses

A:Management avoided providing a direct answer to the outlook for the non-Atlas or EA part of the business next year, stating that it depends on Q3 performance this year. Additionally, they refrained from specifying when AI-related use cases would materially contribute to growth, emphasizing that enterprise AI adoption is still in its early stages.

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Earnings Word Cloud

The most frequently occurring keywords in this quarter's earning call

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