Datadog NASDAQ: DDOG reported third-quarter 2026 revenue of $1.197 billion, up 35% from a year earlier and above the high end of its guidance range, as the cloud monitoring and security provider cited broad demand across its customer base and continued growth from AI-related workloads.
Co-Founder and CEO Olivier Pomel said revenue growth among customers excluding the company’s AI cohort accelerated for a fifth consecutive quarter, reaching the high-20% range year over year. That compared with about 20% growth in the year-ago quarter. The company’s AI customer cohort also continued to expand in both customer count and scale, Pomel said.
Datadog ended the quarter with about 33,500 customers, compared with approximately 32,000 a year earlier. Its number of customers with annual recurring revenue of at least $100,000 rose to about 4,860 from about 4,060, and those larger customers represented roughly 91% of ARR.
Platform adoption and infrastructure milestone
Customer adoption across Datadog’s product portfolio increased during the quarter. The company said 61% of customers used four or more products, up from 54% a year earlier, while 41% used six or more products, compared with 31% a year ago. Customers using at least 10 products doubled to 16% from 8%.
Datadog’s Infrastructure Monitoring suite surpassed $2 billion in ARR and grew at a mid-30% year-over-year rate. Pomel said the business provides visibility across cloud environments, on-premises servers, containers, serverless applications and GPU fleets.
The company also reported a trailing 12-month net revenue retention rate in the low-120% range, similar to the prior quarter. Gross revenue retention remained in the mid- to high-90% range, according to CFO David Obstler.
New customers accounted for approximately 30% of year-over-year revenue growth in the third quarter, up from 25% in the year-earlier period. Obstler said the company has been landing larger new customers and seeing those customers ramp more quickly.
AI products gain adoption
Pomel highlighted investments in both AI capabilities within Datadog’s platform and tools for customers operating AI workloads. He said Bits AI, Datadog’s AI agent, has become the fastest-adopted product in the company’s history. Datadog also made Bits Testing generally available in October, allowing customers to identify critical application flows and generate tests.
The company introduced Scout, a reasoning model optimized for site reliability engineering tasks that now powers Bits Investigation. Pomel said Scout performs on par with or better than frontier models for alert investigations at a lower inference cost, enabling Datadog to investigate more alerts and operate as an always-on first responder.
On the infrastructure side, the number of GPU devices monitored by Datadog increased eightfold so far this year. Spans sent to its Agent Observability product rose ninefold over the same period. More than one-third of Cloud Cost Management customers now track AI costs, while the number of customers doing so increased more than 11 times.
Datadog now serves more than 850 AI customers, up from about 750 in the prior quarter, including 39 spending more than $1 million annually. Pomel said all 15 of the company’s top 15 AI leaders are customers. About one-third of Datadog’s total customer base uses at least one AI product, including roughly three-quarters of customers spending more than $100,000 annually.
Management also pointed to increasing activity around AI agents, saying MCP tool calls increased by a factor of 50 so far this year.
Profitability and outlook
On a non-GAAP basis, Datadog reported gross profit of $972 million and a gross margin of 81.2%, unchanged from the year-earlier period and up from 79.6% in the second quarter. Operating expenses rose 25% year over year, while non-GAAP operating income reached $334 million, representing a 28% operating margin, compared with 23% a year ago.
Cash flow from operations was $290 million, and free cash flow totaled $251 million, or 21% of revenue. Datadog ended the quarter with $5.2 billion in cash equivalents and marketable securities.
- Third-quarter billings were $1.16 billion, up 30% year over year.
- Remaining performance obligations totaled $3.85 billion, up 38% year over year.
- Current RPO grew in the mid-30% range year over year.
For the fourth quarter, Datadog forecast revenue of $1.19 billion to $1.20 billion, representing 25% to 26% growth from a year earlier. The company expects non-GAAP operating income of $280 million to $290 million, implying a 24% operating margin, and non-GAAP earnings per share of $0.69 to $0.71.
For full-year 2026, Datadog expects revenue of $4.515 billion to $4.525 billion, or roughly 32% year-over-year growth. It projected non-GAAP operating income of $1.095 billion to $1.105 billion and non-GAAP EPS of $2.73 to $2.75.
Largest customer and renewal effects
Obstler said Datadog’s largest customer reduced usage during the third quarter but remained above its minimum contractual commitment. The company’s fourth-quarter guidance assumes revenue from that customer at its minimum commitment level.
Management said some large AI customers renewed or extended agreements earlier than expected, receiving improved pricing in exchange for higher commitments. Pomel said those arrangements can create short-term revenue headwinds as customers optimize usage and pricing, but described them as positive developments reflecting customers’ expectations to expand their Datadog deployments.
Datadog said fourth-quarter growth excluding its largest customer is implied to be in the low- to mid-30% range. Obstler also noted that fourth-quarter usage can be affected by late-December vacations and code freezes.
About Datadog (NASDAQ:DDOG)
Datadog, Inc is a technology company that provides a cloud-based monitoring and security platform for applications, infrastructure and other technology environments. Its platform helps organizations collect, analyze and visualize data from servers, databases, containers, cloud services, applications and user interactions in a unified environment.
Datadog's products include infrastructure monitoring, application performance monitoring, log management, real user monitoring, synthetic monitoring, network performance monitoring, cloud security, software delivery tools and incident-management capabilities.
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