Datadog, Inc. (DDOG) Earnings

Management highlights

### Overall Business Growth and Customer Metrics - Total Q2 2026 revenue hit $1.12 billion, up 36% year-over-year, exceeding the high end of prior guidance. Quarter-over-quarter revenue growth was 11%, the highest since Q2 2022, with a record $115 million in quarter-over-quarter revenue additions. - Ended Q2 with 33,400 total customers, up from 31,400 year-over-year, and 4,720 customers with ARR over $100,000, up from 3,850 year-over-year. Trailing 12-month net revenue retention remained in the low 120% range, with gross revenue retention in the mid-to-high 90% range. - Product adoption of the broader Datadog platform continues to increase: 58% of customers use 4+ products (up from 52% year-over-year), 37% use 6+ products (up from 29% year-over-year), and 13% use 10+ products (up from 7% year-over-year). ### Product Innovation and Launches - Held the Dash user conference in Q2, announcing over 100 new products and features, including expanded Bits.ai capabilities to automate the full DevOps loop (detection, root cause identification, fix implementation, continuous learning) and the development loop (code generation, release validation, automated test generation). - Launched a full suite of Datadog for AI products, including data observability for AI training data, agent observability and console, AI Guard security for AI workloads, and Bits Evals to streamline agent development. All 10 of the world's top AI leaders are Datadog customers as of Q2 2026. - Announced expanded infrastructure monitoring capabilities (Network Path and Configuration Management, AI-powered database query optimization), federated log management, Bring Your Own Cloud (BYOC) deployment for logs (with BYOC coming for metrics and traces), infinite cardinality metrics for complex AI workloads with no extra cost, and expanded AI-powered security capabilities that cut vulnerability noise by over 95%. - Named a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms for the sixth consecutive year. Closed a planned acquisition of AI research firm Adaptive ML to accelerate internal AI model development. ### Go-to-Market and Large Deal Wins - Achieved strong new logo dollar bookings, with enterprise new logo annualized bookings more than doubling year-over-year. New customers now contribute 30% of total year-over-year revenue growth, up from 25% in Q1 2026, with new logos ramping faster than historical averages. - Closed multiple large enterprise deals in Q2, including a six-figure annual deal with a Fortune 10 e-commerce company, two seven-figure annual deals with AI neulabs, a seven-figure annual deal with a South American bank, a seven-figure expansion to an eight-figure annual deal with a Fortune 100 health insurer, a $30 million+ total contract value multi-year deal with a large global online media company (displacing four legacy tools, including the largest BYOC deal to date), and a nine-figure annual renewal with a leading AI company. ### AI Strategic Positioning - AI is already a material growth tailwind: Datadog serves over 750 AI customers, with MCP tool call volume quadrupling quarter-over-quarter and growing over 22x compared to Q4 2025. - Datadog addresses three key AI market needs: 1) increasing cloud/AI workload consumption drives higher Datadog platform usage; 2) Bits.ai adds native AI automation to improve customer value; 3) purpose-built Datadog for AI products solve new observability and security challenges introduced by generative AI and agentic workflows. - Internal AI research efforts are accelerating: the company's proprietary TOTO v2 time series model achieved state-of-the-art benchmark performance and demonstrated unprecedented scalability, and the company is developing larger dedicated models to power Bits.ai and support new multi-modal capabilities.

Guidance

- Management maintained its conservative guidance methodology, incorporating the observed usage reduction from the company's largest customer (which renewed in Q2) into Q3 and full-year 2026 guidance to de-risk the outlook. - For Q3 2026, management expects total revenue of $1.135 billion to $1.145 billion, representing 28% to 29% year-over-year growth. Non-GAAP operating income is expected to be $260 million to $270 million (23% to 24% operating margin), and non-GAAP diluted net income per share is expected to be 63 to 65 cents. - For full-year 2026, management expects total revenue of $4.45 billion to $4.47 billion, representing 30% year-over-year growth. Non-GAAP operating income is expected to be $1.01 billion to $1.03 billion (23% operating margin), and non-GAAP diluted net income per share is expected to be $2.50 to $2.54. - Additional full-year 2026 assumptions include: ~$180 million in net interest and other income, $30 million to $40 million in cash taxes, a 21% non-GAAP tax rate, and combined CapEx and capitalized software equal to 4% to 5% of total revenue.

Segment performance

Datadog does not break out formal separate product segments in this call, but reports key product revenue and adoption metrics: 1) RUM (Real User Monitoring) exceeded $200 million in annual revenue, growing over 50% year-over-year. 2) Bits.ai (the company's AI automation suite) has seen rapid expansion across multiple use cases, with broad customer adoption across new and existing customers. 3) Datadog for AI (end-to-end AI observability and security products) serves over 750 AI customers as of Q2 2026, with 31 customers spending over $1 million annually, and 8 of those spending over $10 million annually. Overall total company revenue was $1.12 billion in Q2 2026, with AI-native customers growing rapidly, and non-AI customers growing at 28-29% year-over-year (high 20s), up from mid-20s last quarter and 18% year-over-year in the prior year quarter. Customers with ARR of $100,000 or more contribute 91% of total ARR.

Risks & headwinds

- Forward-looking statements (including guidance) are subject to risks and uncertainties that could cause actual results to differ materially from expectations, with detailed risks outlined in the company's SEC filings (Form 10-Q for Q1 2026, upcoming Q2 2026 Form 10-Q). - Concentration risk with the company's largest customer: the customer renewed the contract, but has experienced reduced usage in recent periods, which is factored into guidance, and future usage changes are outside of management's control. - The AI market is rapidly evolving, and customer priorities and requirements may shift over time as adoption matures, requiring continued product iteration. - CFO customer budget scrutiny remains a consistent factor in sales cycles, requiring the company to continuously demonstrate clear ROI for platform expansion.

Analyst Q&A

• Q: What details can you share on the lower usage from the largest customer after renewal: is it downsell, lower pricing due to volume commitment, or churn? How does this impact underlying business growth? /

  A: Management declines to share specific customer details for confidentiality, but confirms the usage reduction is fully incorporated into guidance to fully de-risk the outlook. Excluding this customer, the rest of the business has seen five straight quarters of continuous acceleration, and the strong underlying business performance is not overshadowed by this single customer dynamic. The contract structure is consistent with standard large enterprise agreements Datadog has always used.

• Q: As AI inference grows to become the dominant AI workload, how much additional observability demand does this create across the stack for Datadog? /

  A: There is material observability opportunity at every layer of the inference stack, from low-level GPU infrastructure monitoring to top-level agent behavior and outcome measurement. Datadog already sees growing adoption of its existing GPU monitoring and agent observability products across both AI neulabs and enterprise customers. Customer priorities have shifted over time: initial focus on validating model correctness has moved to cost optimization, and new priorities will emerge as adoption matures, with Datadog well positioned to address new needs.

• Q: How do CFO-level budget conversations evolve, and does infinite cardinality metrics help address customer cost concerns? /

  A: Datadog has always had to demonstrate clear ROI (either higher revenue or lower cost) to win business, and this dynamic has not changed. As customers adopt AI, they increasingly look to Datadog to help control fast-growing AI infrastructure costs, which aligns with the company's product roadmap. Infinite cardinality addresses a longstanding customer pain point of unpredictable billing from high-cardinality AI workloads, solving the issue both technically and commercially, and has received strong early customer feedback.

• Q: Could Bits.ai automation eventually reduce Datadog consumption by cutting manual observability work, or will it drive higher value and consumption? /

  A: Greater automation creates more value for customers, which leads to more Datadog consumption, not less. The long-term industry shift is from just alerting on issues to automatically fixing them, which increases the value of the Datadog platform. Early adoption shows that customers who use Bits.ai deploy more Datadog products, add more internal users, and increase overall consumption, so it is not a zero-sum dynamic.

• Q: Is the acceleration in non-AI customer growth sustainable, and what is driving it? /

  A: Non-AI growth acceleration is broad-based, driven mostly by existing customers (the majority of the business) from increasing cloud migration workloads and consolidation of multiple legacy tools onto the Datadog platform. The current acceleration is well below the peak growth rates seen in 2021, so it is sustainable. Growth is also supported by continued investments in go-to-market (expanded sales capacity and geographic coverage) that are delivering strong returns, as well as new product innovation that drives upsell.