Datadog’s Q2 results were met with a significant negative market reaction, despite the company delivering revenue and non-GAAP profit above Wall Street’s expectations. Leadership pointed to continued acceleration in both AI-native and traditional customer segments, as well as broad product adoption, as the main drivers of quarterly performance. CEO Olivier Pomel noted, “We continue to see healthy trends in customer demand,” emphasizing that the platform’s usage is expanding across a wide range of customers. However, management acknowledged that a usage reduction by Datadog’s largest customer impacted the quarter and has been factored into their risk assessment and outlook.
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Datadog (DDOG) Q2 CY2026 Highlights:
- Revenue: $1.12 billion vs analyst estimates of $1.08 billion (35.6% year-on-year growth, 3.9% beat)
- Adjusted EPS: $0.65 vs analyst estimates of $0.58 (11.4% beat)
- Adjusted Operating Income: $257 million vs analyst estimates of $233.3 million (22.9% margin, 10.2% beat)
- The company lifted its revenue guidance for the full year to $4.46 billion at the midpoint from $4.32 billion, a 3.2% increase
- Management raised its full-year Adjusted EPS guidance to $2.52 at the midpoint, a 5% increase
- Operating Margin: 0.5%, up from -4.3% in the same quarter last year
- Customers: 4,720 customers paying more than $100,000 annually
- Annual Recurring Revenue: $4.71 billion (35.6% year-on-year growth, beat)
- Billings: $1.18 billion at quarter end, up 38.1% year on year
- Market Capitalization: $86.5 billion
While we enjoy listening to the management’s commentary, our favorite part of earnings calls is the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention.
Our Top 5 Analyst Questions From Datadog’s Q2 Earnings Call
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Sanjit Singh (Morgan Stanley): Asked about the largest customer’s contract renewal and its impact on guidance. CEO Olivier Pomel said usage decreased, so guidance was fully derisked, while CFO David Obstler explained this approach was consistent with prior methodology.
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Raimo Lenschow (Barclays): Inquired about observability needs for AI inference workloads. Pomel explained there are opportunities at every layer of the stack, noting customer focus has shifted from correctness to cost optimization as AI matures.
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Gabriela Borges (Goldman Sachs): Questioned how Datadog addresses CFO concerns about rising observability costs. Pomel highlighted Infinite Cardinality Metrics and evolving product packaging as responses to customer feedback.
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Michael Cikos (Needham): Asked about the ramp in new logo contributions. Obstler clarified that growth from new customers is compounding over time, driven by AI capabilities and broader platform pull-through.
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Ittai Kidron (Oppenheimer & Co.): Sought clarity on customer additions and Bits AI’s role in security automation. Obstler pointed to stable gross additions, while Pomel said Datadog is moving toward broader AI-driven security operations center (SOC) capabilities.
Catalysts in Upcoming Quarters
In the coming quarters, our analyst team will focus on (1) sustained adoption and monetization of new AI observability and security products, (2) customer response to evolving product packaging and cost-management features, and (3) the impact of large enterprise and government wins on overall revenue growth. The pace of Bits AI adoption and progress in federal sector sales will also be important signposts for Datadog’s execution.
Datadog currently trades at $240.45, down from $283.17 just before the earnings. In the wake of this quarter, is it a buy or sell? The answer lies in our full research report (it’s free).
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