Datadog reported a strong Q2 with revenue accelerating 36% YoY, driven by broad-based strength in both AI-native and non-AI customers. Management was bullish on the long-term opportunity from AI and agentic workloads but provided cautious guidance for Q3 due to a usage reduction from their largest customer. Q2 revenue was $1.12B, up 36% YoY, beating guidance, with record quarter-over-quarter revenue growth and strong new logo bookings.
Datadog reported a strong Q2 with revenue accelerating 36% YoY, driven by broad-based strength in both AI-native and non-AI customers. Management was bullish on the long-term opportunity from AI and agentic workloads but provided cautious guidance for Q3 due to a usage reduction from their largest customer. Q2 revenue was $1.12B, up 36% YoY, beating guidance, with record quarter-over-quarter revenue growth and strong new logo bookings.
Revenue growth accelerated, driven by broad-based strength across customer sizes and industries, including non-AI customers growing in the high 20s YoY. New logo bookings doubled YoY in enterprise, and new customers are ramping faster, contributing more to revenue growth.
Management highlighted AI as a significant tailwind, with over 750 AI customers, all top 10 AI leaders as customers, and rapid growth in agentic activity (MCP tool calls quadrupling QoQ). They are expanding AI products (Bits.ai, AI Guard, agent observability) and see AI driving…
Revenue growth accelerated, driven by broad-based strength across customer sizes and industries, including non-AI customers growing in the high 20s YoY. New logo bookings doubled YoY in enterprise, and new customers are ramping faster, contributing more to revenue growth.
Management highlighted AI as a significant tailwind, with over 750 AI customers, all top 10 AI leaders as customers, and rapid growth in agentic activity (MCP tool calls quadrupling QoQ). They are expanding AI products (Bits.ai, AI Guard, agent observability) and see AI driving…
Management highlighted AI as a significant tailwind, with over 750 AI customers, all top 10 AI leaders as customers, and rapid growth in agentic activity (MCP tool calls quadrupling QoQ). They are expanding AI products (Bits.ai, AI Guard, agent observability) and see AI driving broader cloud and platform usage.
Revenue growth accelerated, driven by broad-based strength across customer sizes and industries, including non-AI customers growing in the high 20s YoY. New logo bookings doubled YoY in enterprise, and new customers are ramping faster, contributing more to revenue growth.
Management expects CapEx and capitalized software together to be in the 4% to 5% of revenue range for fiscal 2026, with no significant change discussed.
Management emphasized broad-based acceleration, strong product innovation, and solid execution, while proactively addressing the largest customer headwind.
“We did see a reduction in usage and we took the liberty to fully de-risk the guidance for the rest of the year with respect to that customer... the business is booming and we don't want that to overshadow basically the acceleration we see…”
“We're also seeing signs of rapid growth in agentic activity with a number of MCP tool calls quadrupling again quarter over quarter and growing more than 22x when compared to Q4 2025.”
“The focus has moved quite a bit towards cost. Now customers were spending a lot on AI and they were wondering what to optimize cost... We see growing adoption from the products we already have there... We're also seeing an explosion of vol…”
| 지표 | 기간 | 범위 | 중간값 | 상태 |
|---|---|---|---|---|
| Capex | FY2026 | 4%–5% | 4.5% | GUIDED |
| EPS | FY2026 | $2.50–$2.54 | $2.52 | GUIDED |
| EPS | FY2026 Q3 | $0.63–$0.65 | $0.64 | GUIDED |
| Op margin | FY2026 | 23% | 23% | GUIDED |
| Op margin | FY2026 Q3 | 23%–24% | 23.5% | GUIDED |
| Revenue | FY2026 Q3 | $1.135B–$1.145B | $1.14B | GUIDED |
| Revenue | FY2026 | $4.45B–$4.47B | $4.46B | RAISED |
| 제시 시점 | 지표 | 목표 기간 | 가이던스 | 실제 | 결과 |
|---|---|---|---|---|---|
| FY2026 Q1 | EPS | FY2026 Q2 | $0.57–$0.59 | $0.65 | Met / beat |
| FY2026 Q1 | Op margin | FY2026 Q2 | 21%–22% | 0.49% | Missed |
| FY2026 Q1 | Revenue | FY2026 Q2 | $1.07B–$1.08B | $1.1215B | Met / beat |
| FY2025 Q4 | EPS | FY2026 Q1 | $0.49–$0.51 | $0.60 | Met / beat |
| FY2025 Q4 | Op margin | FY2026 Q1 | 21% | 0.73% | Missed |
| FY2025 Q4 | Revenue | FY2026 Q1 | $0.951B–$0.961B | $1.0064B | Met / beat |
Being a customer of all top 10 AI leaders, including Anthropic, validates Datadog's platform in the AI sector, but the quote is aggregated and does not detail specific usage or revenue from Anthropic.
“When we look at the largest companies driving AI, all 10 of the top 10 AI leaders are Datadog customers.”
Turning to product adoption, our platform strategy continues to resonate in the market.
… with a leading AI company. This longtime, very large customer uses 17 Datadog products to enable unified visibility on production workloads at a very large scale. albeit with a user introduction starting in Q3 which we consider in our guidance and which David will speak to. Before I turn it over to David for a financial review, let me offer a few words on our longer-term outlook. There is no change to our overall view that digital transformation and cloud migration are long-term security growth drivers for our business. But we now have an additional growth driver with AI as we help our customers deliver value with this transformative new technology. We are tremendously excited about our opportunities in AI. To summarize where we are and where we're going. First, AI is a tailwind for Datadog today as cloud consumption grows and drives more users of our platform. As of Q2, over 750 AI customers use Datadog to monitor and improve their tech stacks. When we look at the largest companies driving AI, all 10 of the top 10 AI leaders are Datadog customers. Beyond AI natives, we see AI activity growing across our broader customer base. We're also seeing signs of rapid growth in agentic activity with a number of MCP tool calls quadrupling again quarter over quarter and growing more than 22x when compared to Q4 2025. Second, We are delivering AI for Datadog to deliver more value and greater platform capability to our customers. This includes our Bits.ai products, chat, investigation, detection, code, testing, release, and many, many others. Third, next-gen AI introduces new complexity and observability challenges. We are addressing this with what we call Datadog for AI to observe and secure the AI stack from end to end. This includes GPU monitoring, Agent Observability, Agent Console, Data Observability, AI Guard, and many other products. Finally, our AI research team and our large volume of rich data using critical workflows enable us to conduct groundbreaking research. We have shown some of our work already with the second version of our time series model, TOTO, in May. TOTO version 2 was exciting for two reasons. First, we've shown it to be state-of-the-art on key benchmarks. but more importantly, we've demonstrated for the first time true scalability for time series models, allowing us to target the same improvement path language models have followed since …
Datadog's integration with Databricks expands its interoperability, potentially making it easier for mutual customers to use both platforms together, though it also signals Databricks' data is a valuable source for observability.
“In log management, Federating logs enables users to query external data stores, including Databricks and Clickhouse.”
Turning to product adoption, our platform strategy continues to resonate in the market.
… companies to trust the data being used by AI with lineage quality monitoring and jobs monitoring. Base data analysis uses a rich data context to accurately answer business questions. And agent console provides visibility into AI agent usage, cost, and effectiveness. In agent observability, our patterns capability automatically clusters user interactions into behavioral groups to identify quality or cost issues. And Bits Evals handles the repetitive parts of the agent development loop in order to improve the outcomes of agents. We are broadening our platform to ingest, correlate, analyze, and act on more data, whether on-prem or in the cloud. In network monitoring, we launched Network Path and Network Configuration Management to trace changes that cause complex network issues. Within database monitoring, Bits Database Optimizer now automatically simulates and evaluates the impact of AI-generated changes in order to optimize slow queries. In log management, Federating logs enables users to query external data stores, including Databricks and Clickhouse. And with Bring Your Own Cloud, or BYOC, customers can now use a full Datadog experience on logs that are kept within their infrastructure. And we've also announced that we're bringing BYOC to metrics and traces as well. In the digital experience space, journey monitoring automatically gives a single shared view for every critical user flow. And for custom metrics data, We introduced infinite cardinality metrics which allow our users to answer arbitrarily complex questions as they generate larger amounts of data with AI agents without incurring any extra costs. Finally, we launched a number of innovations to secure the AI stack and defend against a new class of AI-powered attacks. AI Guard agent discovery finds and maps every known and unknown custom agent so security teams can see what is protected and what is not. AI Guard for Custom Agents provides runtime protections to block attacks that can only be detected with real-time observability data. AI Guard for Coding Agents applies the same deep observability to block malicious skills and packages in code. And we also announced runtime priorities as an engine to cut vulnerability noise by over 95%. And finally, we expanded Bits Security Analyst to run on non-datadog themes So customers can benefit from the smarts and the learnings of our broad dataset, …