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Datadog (DDOG) investor relations material

Datadog Q3 2025 earnings summary

Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.
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Q3 2025 earnings summary6 Nov, 2025

Executive summary

  • Q3 2025 revenue reached $886 million, up 28% year-over-year, exceeding guidance and driven by strong demand, large customer growth, and over 1,000 platform integrations.

  • Customer base grew to 32,000, with 4,060 customers generating $100,000+ ARR, accounting for 89% of ARR.

  • AI-native customer revenue accelerated, with 12% of total revenue from this group, up from 6% a year ago.

  • Platform adoption deepened, with 84% of customers using two or more products and 16% using eight or more.

  • Expanded AI observability and security offerings, recognized as a leader in Gartner's Magic Quadrant for Digital Experience Monitoring.

Financial highlights

  • Free cash flow was $214 million in Q3, with a 24% margin; operating cash flow for the nine months was $723.1 million.

  • Gross margin for Q3 was 81.2% non-GAAP and 80% GAAP.

  • Non-GAAP operating income was $207 million (23% margin); GAAP operating loss was $6 million.

  • Billings grew 30% year-over-year to $893 million; RPO rose 53% to $2.79 billion.

  • Trailing 12-month net revenue retention was 120%; gross revenue retention remained in the mid to high 90s.

Outlook and guidance

  • Q4 2025 revenue expected between $912–$916 million, up 24% year-over-year.

  • Q4 non-GAAP operating income projected at $216–$220 million (24% margin); EPS $0.54–$0.56.

  • FY25 revenue guidance raised to $3.386–$3.390 billion, up 26% year-over-year.

  • FY25 non-GAAP operating income expected at $754–$758 million (22% margin); EPS $2.00–$2.02.

  • Capital expenditures and capitalized software to be 4% of revenues in FY25.

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Frequently asked questions

Data’s Best Friend

Datadog is an American company that provides a service for cloud-scale monitoring and analytics, primarily catering to IT, operations, and development teams. Datadog's services include monitoring servers, databases, tools, and services through a SaaS-based data analytics platform. This platform allows users to track the performance of their applications, understand user behavior, and identify bottlenecks or issues in real-time. The company is headquartered in NYC, and its shares are listed on the Nasdaq.

Solving Challenges

Datadog was founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, both experienced technologists with a vision to improve IT infrastructure monitoring. While working together Pomel, and Lê-Quôc observed the challenges organizations faced in monitoring increasingly complex, cloud-based systems. To address this, they created a platform that could provide comprehensive, real-time insights into the performance of IT systems, regardless of their complexity or scale. Initially focusing on cloud infrastructure monitoring, Datadog has expanded its product suite to cover a wide range of monitoring and analytics services. Today, Datadog is well-established and competes with companies such as Splunk, New Relic, and Dynatrace.

SaaS

Datadog operates as a cloud-monitoring service through a SaaS model, offering a range of tools for observing and optimizing the performance of IT infrastructure, applications, and services. The company provides a platform that aggregates data across various systems, enabling real-time analytics and insights. This functionality allows IT and development teams to monitor server health, track application performance, and analyze logs and user experiences. Its services cater to various aspects of technology management, including infrastructure monitoring, application performance management (APM), and log management.

The Customers

Datadog caters to a diverse range of customers, spanning from small startups to large enterprises across various industries. This includes technology companies, financial services, healthcare organizations, e-commerce platforms, and media companies, among others. The platform's scalability and comprehensive toolset make it particularly attractive to businesses undergoing digital transformation or managing complex, multi-cloud environments

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