Datadog, Inc. Q4 FY2025 earnings call

• Business drivers: There are broad-based positive trends in the demand environment. Revenue growth is accelerating, driven by the broad-based business outside AI-native customers and high growth within AI-native groups. The go-to-market teams achieved a record $1.63 billion in bookings, up 37% year over year, with large deals signed. Churn remains low with gross revenue retention in the mid to high nineties.
• Q4 financial performance: Revenue was $953 million, an increase of 29% year over year, above the high end of the guidance range. Ended Q4 with about 32,700 customers, and about 4,310 customers with an ARR of $100,000 or more, which generated about 90% of the ARR. Free cash flow was $291 million with a free cash flow margin of 31%.
• Product adoption: At the end of Q4, 84% of customers used two or more products, 55% used four or more products, 33% used six or more products, 18% used eight or more products, and 9% used 10 or more products, showing increased platform penetration.
• Product innovations: Over 400 new features and capabilities were released in 2025. AI efforts include AI for Datadog (improving the Datadog platform for customers) and Datadog for AI (enabling observability across customers' AI stacks). Launched the AI SRE agent for general availability, DeepAI DevAgent, BigAI Security, etc.
• Sales wins: There were multiple large deals closed, including 18 deals over $10 million in TCV, two over $100 million, and an 8-figure land with a leading AI model company, demonstrating strong customer adoption and consolidation.

Infrastructure monitoring contributed over $1.6 billion in ARR. Log management is now over $1 billion in ARR. The end-to-end suite of APM and DEM products also crossed $1 billion in ARR. Infrastructure monitoring's ARR is over $1.6 billion, log management over $1 billion, and the APM/DEM suite over $1 billion, with these segments significantly contributing to the overall revenue.

• First quarter 2026: Revenue is expected to be in the range of $951 to $961 million, representing a 25% to 26% year-over-year growth. Non-GAAP operating income is expected to be in the range of $195 to $205 million, implying an operating margin of 21%. Non-GAAP net income per share is expected to be in the $0.49 to $0.51 per share range.
• Full fiscal year 2026: Revenue is expected to be in the range of $4.06 to $4.1 billion, representing 18% to 20% year-over-year growth. Non-GAAP operating income is expected to be in the range of $840 million to $880 million, implying an operating margin of 21%. Non-GAAP net income per share is expected to be in the range of $2.08 to $2.16 per share. Expect net interest and other income for fiscal year 2026 to be approximately $140 million, cash taxes in 2026 to be about $30 million to $40 million, a 21% non-GAAP tax rate for 2026 and beyond, and capital expenditures and capitalized software together to be in the 4% to 5% of revenue range.

Subject to a variety of risks and uncertainties that could cause actual results to differ materially, including those discussed in the Form 10-Q for the quarter ended 09/30/2025 and other filings with the SEC.

Q: Sanjit Singh with Morgan Stanley asked about observability in the context of agentic frameworks and how Datadog may evolve.

A: Olivier Pomel discussed that observability is an accelerant, there will be more automation, and Datadog is building products to satisfy both human UIs and agent interactions.

Q: Raimo Lenschow with Barclays asked about the 8-figure deal with a model company and what drove the customer's thinking.

A: Olivier Pomel said customers see value in Datadog over open-source/tools as engineers' velocity is crucial for business.

Q: Gabriela Borges with Goldman Sachs asked about LLM as an anomaly detection tool and value creation with Datadog.

A: Olivier Pomel talked about observability needing to be proactive and embedded in the data plane.

Q: Ittai Kidron with Oppenheimer and Company asked about the conservatism in the guidance and the AI cohort.

A: David Obstler discussed the conservative guidance based on organic growth rates and the diversified customer base.

Q: Todd Coupland with CIBC asked about competition and the impact of the LLM rise.

A: Olivier Pomel said competition remains unchanged and Datadog is well-positioned.

Q: Mark Murphy with JPMorgan asked about CapEx and diversifying AI customers.

A: Olivier Pomel and David Obstler talked about CapEx indicating increased complexity and Datadog diversifying its AI customer base.

Q: Matt Hedberg with RBC asked about gross margin expectations and AI internal investment.

A: David Obstler said they are balancing investment and efficiency, and using AI internally for productivity.

Q: Howard Ma with Guggenheim asked about the growth of the core APM product and its drivers.

A: Olivier Pomel said APM growth is due to simplified onboarding, digital experience, and go-to-market investment.

Q: Peter Weed with Bernstein Research asked about Bits AI and competition.

A: Olivier Pomel talked about value from time saved and Datadog's advantage in in-stream analysis.

Q: Brent Thill with Jefferies asked about the margin and go-to-market.

A: David Obstler discussed conservative revenue planning and continuing go-to-market growth.