Datadog, Inc. Class A Common Stock 2026 Q2 Earnings Call

Good morning. Thank you for joining us to review Datadog's second quarter 2026 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog's Co-founder and CEO, and David Obstler, Datadog's CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the third quarter and the fiscal year 2026, and related notes and assumptions, our product capabilities, and our ability to capitalize on market opportunities. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially.

For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended March 31st, 2026. Additional information will be made available on our upcoming Form 10-Q for the fiscal quarter ending June 30th, 2026, and other filings with the SEC. This information is also available in the investor relations section of our website, along with a replay of this call. We will discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com. With that, I'd like to turn the call over to Olivier.

Thanks, Yuka. Thank you all for joining us to go over our Q2 results. Let me begin with this quarter's business drivers. Our revenue growth in Q2 has accelerated across our customer base. On one hand, our AI native customer cohort continued to grow and diversify, both in the number of customers we serve and the scale of those customers. On the other hand, and as a great illustration of the breadth of trends across our business, revenue growth for our non-AI customers also accelerated again this quarter to the high 20s% year-over-year, up from the mid-20s last quarter and 18% year-over-quarter. Overall, we continue to see healthy trends in customer demand. Our broad base of customers, from the most nimble startups to the largest and most established enterprises, are all adopting AI.

We think this is accelerating their usage of cloud and modern technologies, as well as their usage of the Datadog platform to observe, secure, and act on their cloud and AI workloads. Regarding our Q2 financial performance and key metrics, revenue was $1.12 billion, an increase of 36% year-over-year and above the high end of our guidance range. We ended Q2 with about 33,400 customers, up from about 31,400 a year ago. We also ended with about 4,720 customers with an ARR of $100,000 or more, up from about 3,850 a year ago. These customers generated about 91% of our ARR. We generated free cash flow of $279 million with a free cash flow margin of 25%. Turning to product adoption. Our platform strategy continues to resonate in the market.

For example, 58% of our customers now use four or more products, up from 52% a year ago. 37% of our customers use six or more products, up from 29% a year ago, and 13% of our customers use 10 or more products, up from 7% a year ago. We're landing more customers and delivering value across more products, our products are broadly delivering strong growth in usage and ARR. As an example, RUM, or Real User Monitoring, now exceeds $200 million in ARR and accelerated at its scale to over 50% growth year-over-year. Our customers are sending more user sessions and using RUM in conjunction with our newer Product Analytics to optimize their business outcomes. Moving on to R&D. We held our DASH user conference in June, where we announced over 100 exciting new products and features for our users.

Let's go through some of the announcements. First, we expanded Bits AI to accelerate and automate the DevOps loop. This is the loop that goes from detection to investigation to remediation that engineers go through each time something breaks. At DASH, we announced a lot of new Bits capabilities for the DevOps loop. Bits can now create and maintain monitors, identify root causes within minutes of a negative signal, recommend and implement fixes, follow guardrails to add safety and controls, continuously learn and improve from prior incidents, and detect symptomatic behaviors early to repair infrastructure issues before they escalate. Second, we announced Bits AI products to address the development loop. This is the loop that goes from coding to delivery to evaluation that developers navigate to get code to production.

For this loop, Bits Release now acts as an AI release validation agent, analyzing the impact of code changes, running end-to-end checks, and verifying production rollouts. Bits Code generates code fixes, guaranteeing every fix and reproduction behavior, Bits Testing also automates synthetic test generation and maintenance. Third, we expanded Datadog for AI, our products that observe, secure, and optimize the AI stack from end to end. Data Observability enables companies to trust the data being used by AI with lineage quality monitoring and jobs monitoring. Bits Data Analysis uses a rich data context to accurately answer business questions. Agent Console provides visibility into AI agent usage, cost, and effectiveness. In Agent Observability, our patterns capability automatically clusters user interactions into behavior groups to identify quality or cost issues. Bits Evals handles the repetitive parts of the agent development loop in order to improve the outcomes of agents.

Fourth, 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. With Bring Your Own Cloud, or BYOC, customers can now use the full Datadog experience on logs that are kept within their infrastructure. 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.

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. We also announced Runtime Prioritization Engine to cut vulnerability noise by over 95%.

Finally, we expanded Bits Security Analyst to run on known Datadog Cloud SIEMs so customers can benefit from the smarts and the learnings of a broad data set regardless of which SIEM they deploy. As we continue to innovate, we are being rightfully recognized by independent research. We are pleased to see that for the sixth year in a row, Datadog has been named a leader in the 2026 Gartner Magic Quadrant for Observability Platforms. Let's move on to sales and marketing and look at a few of the deals our GTM teams have closed in what has been a very strong quarter. First, we landed a six-figure annualized deal with a Fortune 10 company. This company is expanding its e-commerce business, and they plan to use Datadog Log Management alongside 10 other Datadog products to improve customer experience and business outcomes.

This win validates our expanded go-to-market approach to focus on the world's largest companies and win opportunities in the most complex environments. Next, we landed seven-figure annualized deals with two neuro labs. These AI labs are rapidly scaling their AI model training workloads and preparing for major product launches. By deploying observability using Datadog, they gain visibility across their training infrastructure and GPU fleets and can iterate faster on their AI models. They are also using Bits AI to rapidly build monitors, dashboards, and alerts for deep observability context. Next, we landed a seven-figure annualized deal with a South American bank. This bank's fragmented legacy monitoring stack and manual triaging caused significant application downtime that was often called in by customers.

By consolidating into Datadog with 11 products, this customer enables visibility from their mainframe all the way to their microservices and has already reduced mean time to resolution on live production incidents. They are adopting Cloud SIEM and Data Security and evaluating other Datadog security products to improve their security posture. Next, we signed a seven-figure annualized expansion for an eight-figure annualized deal with a Fortune 100 health insurance company. This customer's biggest pain point is to deliver great experience to their members throughout their care while protecting PII across dozens of business units. Datadog's HIPAA compliance and PII handling in RUM, Log Management, and Cloud SIEM allowed us to differentiate and win over competitive solutions. Bits AI investigation is already speeding up incident resolution and reducing expensive escalations. This customer will expand to 19 Datadog products.

We signed a multiyear, over $30 million TCV deal with one of the world's largest online media companies. This customer chose to standardize on Datadog across its business, displacing four commercial and internal tools. Datadog also proved value beyond core observability with Product Analytics, CI Visibility, Data Observability, and Cloud Cost Management. This deal includes our largest win to date for Bring Your Own Cloud, displacing their legacy commercial logging tool at a petabyte scale. Finally, we signed a nine-figure renewal 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 reduction starting in Q3, which we considered 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.