Datadog Announces First Quarter 2026 Financial Results

First quarter revenue grew 32% year-over-year to $1,006 million

Robust growth of larger customers, with about 4,550 $100k+ ARR customers, up from about 3,770 a year ago

Launched MCP Server, Bits AI Security Agent, GPU Monitoring, and Experiments for general availability

NEW YORK, May 07, 2026 (GLOBE NEWSWIRE) -- Datadog, Inc. (NASDAQ:DDOG), the leading AI-powered observability and security platform, today announced financial results for its first quarter ended March 31, 2026.

"Datadog executed to a strong quarter, with 32% year-over-year revenue growth, $335 million in operating cash flow, and $289 million in free cash flow," said Olivier Pomel, co-founder and CEO of Datadog. "We are helping customers of all sizes and industries deploy modern, cloud-based, AI-enabled solutions."

Pomel added, "We're using AI to build rapidly across the Datadog platform, and are excited to showcase our latest innovations at our DASH user conference in June."

First Quarter 2026 Financial Highlights:

• Revenue was $1,006 million, an increase of 32% year-over-year.

• GAAP operating income was $7 million; GAAP operating margin was 1%.

• Non-GAAP operating income was $223 million; non-GAAP operating margin was 22%.

• GAAP net income per diluted share was $0.15; non-GAAP net income per diluted share was $0.60.

• Operating cash flow was $335 million, with free cash flow of $289 million.

• Cash, cash equivalents, and marketable securities were $4.8 billion as of March 31, 2026.

First Quarter & Recent Business Highlights:

• As of March 31, 2026, we had about 4,550 customers with ARR of $100,000 or more, an increase of 21% from about 3,770 as of March 31, 2025.
  
  

• Achieved FedRAMP High certification for Datadog for Government, one of the federal government’s most stringent cloud security and compliance standards—reinforcing Datadog’s commitment to serving highly sensitive federal environments and enabling U.S. government agencies and contractors to adopt modern observability for secure workloads.
  
  

• Launched GPU Monitoring for generally availability, to help businesses optimize spend and performance as they scale AI projects—providing unified visibility across GPU fleet health, cost, and performance linked directly to the teams and workloads consuming those resources, enabling faster troubleshooting and cost savings.
  
  

• Released the State of AI Engineering 2026 Report, which found that operational complexity—not model intelligence—is becoming the primary barrier to reliable AI at scale, with nearly 5% of AI model requests failing in production and close to 60% of those failures caused by capacity limits.
  
  

• Launched Datadog Experiments, which embeds experimentation into observability to help teams design, measure, and optimize product A/B tests directly within the Datadog platform—pairing best-in-class statistical methods with real-time observability guardrails so companies can ship with confidence.
  
  

• Delivered Bits AI Security Analyst to general availability as part of Datadog’s Cloud SIEM, enabling security teams to reduce threat investigation time by up to 98% by autonomously analyzing alerts with the depth and expertise of a senior SOC analyst at machine scale and speed.
  
  

• Announced the general availability of Datadog's MCP Server, which provides AI coding agents and IDEs with secure, real-time access to unified observability data—enabling faster debugging, safer automation, and governed AI operations at scale.
  
  

• Appointed Dominic Phillips to Datadog’s Board of Directors. Phillips brings more than two decades of financial leadership in the technology sector, including his current role as Executive Vice President and Chief Financial Officer at Samsara and previous positions at ServiceNow and Morgan Stanley.
  
  

• Published the 2026 State of DevSecOps Report, which found that 87% of organizations are running software with known, exploitable vulnerabilities—highlighting a broader industry shift as security risk increasingly moves upstream into the software supply chain.
  
  

• Entered into a strategic partnership with Sakana AI, a next-generation AI research lab, to collaborate on research, product innovation, and go-to-market initiatives focused on enterprise AI adoption—initially supporting large enterprise customers in Japan before expanding globally.
  
  

• Opened registration for DASH 2026, Datadog’s ninth annual global conference for builders, engineers, security leaders, and technology decision-makers exploring how observability and security are evolving in an era of increasingly complex, AI-driven systems. The conference will take place June 9-10 at the North Javits Center in New York City.
  

Second Quarter and Full Year 2026 Outlook:

Based on information as of today, May 7, 2026, Datadog is providing the following guidance:

• Second Quarter 2026 Outlook:

  • Revenue between $1.07 billion and $1.08 billion.

  • Non-GAAP operating income between $225 million and $235 million.

  • Non-GAAP net income per share between $0.57 and $0.59, assuming approximately 369 million weighted average diluted shares outstanding.

• Full Year 2026 Outlook:

  • Revenue between $4.30 billion and $4.34 billion.

  • Non-GAAP operating income between $940 million and $980 million.

  • Non-GAAP net income per share between $2.36 and $2.44, assuming approximately 372 million weighted average diluted shares outstanding.

Datadog has not reconciled its expectations as to non-GAAP operating income, or as to non-GAAP net income per share, to their most directly comparable GAAP measure as a result of uncertainty regarding, and the potential variability of, reconciling items such as stock-based compensation and employer payroll taxes on equity incentive plans. Accordingly, reconciliation is not available without unreasonable effort, although it is important to note that these factors could be material to Datadog’s results computed in accordance with GAAP.

Conference Call Details:

• What: Datadog financial results for the first quarter of 2026 and outlook for the second quarter and the full year 2026

• When: May 7, 2026 at 8:00 A.M. Eastern Time (5:00 A.M. Pacific Time)

• Dial in: To access the call in the U.S., please register here. Callers are encouraged to dial into the call 10 to 15 minutes prior to the start to prevent any delay in joining.

• Webcast: https://investors.datadoghq.com (live and replay)

• Replay: A replay of the call will be archived on the investor relations website
  

About Datadog

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence.

Forward-Looking Statements

This press release and the earnings call referencing this press release contain “forward-looking” statements, as that term is defined under the federal securities laws, including but not limited to statements regarding Datadog’s strategy, product and platform capabilities, the growth in and ability to capitalize on long-term market opportunities including the pace and scope of cloud migration, digital transformation and AI deployment, gross margins, operating margins including with respect to sales and marketing, research and development expenses, net interest and other income, cash taxes, capital expenditures and capitalized software, and Datadog’s future financial performance, including its outlook for the second quarter and the full year 2026 and related notes and assumptions. These forward-looking statements are based on Datadog’s current assumptions, expectations and beliefs and are subject to substantial risks, uncertainties, assumptions and changes in circumstances that may cause Datadog’s actual results, performance or achievements to differ materially from those expressed or implied in any forward-looking statement.

The risks and uncertainties referred to above include, but are not limited to (1) our recent rapid growth may not be indicative of our future growth; (2) our history of operating losses; (3) our limited operating history; (4) our dependence on existing customers purchasing additional subscriptions and products from us and renewing their subscriptions; (5) our ability to attract new customers; (6) our ability to effectively develop and expand our sales and marketing capabilities; (7) risk of a security breach; (8) risk of interruptions or performance problems associated with our products and platform capabilities; (9) our ability to adapt and respond to rapidly changing technology or customer needs; (10) the competitive markets in which we participate; (11) risks associated with successfully managing our growth; (12) risks associated with changing laws, regulations, and contractual obligations related to data privacy and security and (13) general market, political, economic, and business conditions including concerns about trade policies, tariffs, reduced economic growth and associated decreases in information technology spending. These risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission (SEC), including in the section entitled “Risk Factors” in our Annual Report on Form 10-K for the year ended December 31, 2025, filed with the SEC on February 18, 2026. Additional information will be made available in our Quarterly Report on Form 10-Q for the quarter ended March 31, 2026 and other filings and reports that we may file from time to time with the SEC. Moreover, we operate in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for our management to predict all risks, nor can we assess the impact of all factors on our business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements we may make. In light of these risks, uncertainties and assumptions, we cannot guarantee future results, levels of activity, performance, achievements, or events and circumstances reflected in the forward-looking statements will occur. Forward-looking statements represent our beliefs and assumptions only as of the date of this press release. We disclaim any obligation to update forward-looking statements.

About Non-GAAP Financial Measures

Datadog discloses the following non-GAAP financial measures in this release and the earnings call referencing this press release: non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (research and development, sales and marketing and general and administrative), non-GAAP operating income (loss), non-GAAP operating margin, non-GAAP net income (loss), non-GAAP net income (loss) per diluted share, non-GAAP net income (loss) per basic share, free cash flow and free cash flow margin. Datadog uses each of these non-GAAP financial measures internally to understand and compare operating results across accounting periods, for internal budgeting and forecasting purposes, for short- and long-term operating plans, and to evaluate Datadog’s financial performance. Datadog believes they are useful to investors, as a supplement to GAAP measures, in evaluating its operational performance, as further discussed below. Datadog’s non-GAAP financial measures may not provide information that is directly comparable to that provided by other companies in its industry, as other companies in its industry may calculate non-GAAP financial results differently, particularly related to non-recurring and unusual items. In addition, there are limitations in using non-GAAP financial measures because the non-GAAP financial measures are not prepared in accordance with GAAP and may be different from non-GAAP financial measures used by other companies and exclude expenses that may have a material impact on Datadog’s reported financial results.

Non-GAAP financial measures should not be considered in isolation from, or as a substitute for, financial information prepared in accordance with GAAP. A reconciliation of the historical non-GAAP financial measures to their most directly comparable GAAP measures has been provided in the financial statement tables included below in this press release.

Datadog defines non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (research and development, sales and marketing and general and administrative), non-GAAP operating income (loss), non-GAAP operating margin and non-GAAP net income (loss) as the respective GAAP balances, adjusted for, as applicable: (1) stock-based compensation expense; (2) the amortization of acquired intangibles; (3) employer payroll taxes on employee stock transactions; (4) M&A transaction costs; (5) amortization of issuance costs; and (6) an assumed provision for income taxes based on our long-term projected tax rate. Non-GAAP financial measures prior to April 1, 2025 have not been adjusted for M&A transaction costs, as such costs were not material to our results of operations in such prior periods. Our estimated long-term projected tax rate is subject to change for a variety of reasons, including the rapidly evolving global tax environment, significant changes in Datadog's geographic earnings mix, or other changes to our strategy or business operations. We will re-evaluate our long-term projected tax rate as appropriate. Datadog defines free cash flow as net cash provided by operating activities, minus capital expenditures and minus capitalized software development costs, if any. Investors are encouraged to review the reconciliation of these historical non-GAAP financial measures to their most directly comparable GAAP financial measures.

Management believes these non-GAAP financial measures are useful to investors and others in assessing Datadog’s operating performance due to the following factors:

Stock-based compensation. Datadog utilizes stock-based compensation to attract and retain employees. It is principally aimed at aligning their interests with those of its stockholders and at long-term retention, rather than to address operational performance for any particular period. As a result, stock-based compensation expenses vary for reasons that are generally unrelated to financial and operational performance in any particular period.

Amortization of acquired intangibles. Datadog views amortization of acquired intangible assets as items arising from pre-acquisition activities determined at the time of an acquisition. While these intangible assets are evaluated for impairment regularly, amortization of the cost of acquired intangibles is an expense that is not typically affected by operations during any particular period.

Employer payroll taxes on employee stock transactions. Datadog excludes employer payroll tax expense on equity incentive plans as these expenses are tied to the exercise or vesting of underlying equity awards and the price of Datadog’s common stock at the time of vesting or exercise. As a result, these taxes may vary in any particular period independent of the financial and operating performance of Datadog’s business.

M&A transaction costs. Datadog views acquisition-related expenses, such as transaction costs, as costs that are not necessarily reflective of operational performance during a period. In particular, Datadog believes the consideration of measures that exclude such expenses can assist in the comparison of operational performance in different periods which may or may not include such expenses.

Amortization of issuance costs. In June 2020 and December 2024, Datadog issued $747.5 million of 0.125% convertible senior notes due 2025 and $1.0 billion of 0% convertible senior notes due 2029, respectively. Debt issuance costs, which reduce the carrying value of the convertible debt instrument, are amortized as interest expense over the term. The expense for the amortization of debt issuance costs is a non-cash item, and we believe the exclusion of this interest expense will provide for a more useful comparison of our operational performance in different periods.

Additionally, Datadog’s management believes that the non-GAAP financial measure free cash flow is meaningful to investors because it is a measure of liquidity that provides useful information in understanding and evaluating the strength of our liquidity and future ability to generate cash that can be used for strategic opportunities or investing in our business. Free cash flow represents net cash provided by operating activities, reduced by capital expenditures and capitalized software development costs, if any. The reduction of capital expenditures and amounts capitalized for software development facilitates comparisons of Datadog's liquidity on a period-to-period basis and excludes items that management does not consider to be indicative of our liquidity.

Operating Metrics

Datadog’s number of customers with ARR of $100,000 or more is based on the ARR of each customer, as of the last month of the quarter.

We define the number of customers as the number of accounts with a unique account identifier for which we have an active subscription in the period indicated. Users of our free trials or tier are not included in our customer count. A single organization with multiple divisions, segments or subsidiaries is generally counted as a single customer. However, in some cases where they have separate billing terms, we may count separate divisions, segments or subsidiaries as multiple customers.

We define ARR as the annualized revenue run-rate of subscription agreements from all customers at a point in time. We calculate ARR by taking the monthly recurring revenue, or MRR, and multiplying it by 12. MRR for each month is calculated by aggregating, for all customers during that month, monthly revenue from committed contractual amounts, additional usage, usage from subscriptions for a committed contractual amount of usage that is delivered as used, and monthly subscriptions. ARR and MRR should be viewed independently of revenue, and do not represent our revenue under GAAP on a monthly or annualized basis, as they are operating metrics that can be impacted by contract start and end dates and renewal rates. ARR and MRR are not intended to be replacements or forecasts of revenue.

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Contact Information
Yuka Broderick
Datadog Investor Relations
IR@datadoghq.com

Dan Haggerty
Datadog Public Relations
Press@datadoghq.com

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