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Edge16 Oct 2026
Winner, Winner: The Chicken McNugget Story
How a 1940s breeding contest, a Cornell food scientist, and a hedge by Ray Dalio helped McDonald's turn the Chicken McNugget into a fast-food icon.
Datadog
Datadog (DDOG) investor relations material
Datadog Q3 2026 earnings summary
Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.Q3 2026 earnings summary4 Nov, 2026
Executive summary
Q3 revenue grew 35% YoY to $1.197B, above the high end of guidance.
Non-AI customer revenue growth accelerated for a fifth consecutive quarter to the high-20% range, while AI customers remained a major growth driver.
GAAP net income was $118.3M versus $33.9M a year earlier; non-GAAP net income was $304.3M versus $197.4M.
Cloud migration, digital transformation and AI adoption were cited as long-term growth drivers.
Usage from the largest customer declined in Q3, creating potential revenue-growth deceleration.
Financial highlights
Billings were $1.16B, up 30%, and RPO was $3.85B, up 38%.
GAAP gross profit was $959.9M versus $709.2M; non-GAAP gross profit was $972M.
GAAP operating income was $74.7M versus a $5.8M loss; non-GAAP operating income was $334.3M versus $207.4M.
GAAP diluted EPS was $0.32 versus $0.10; non-GAAP diluted EPS was $0.81 versus $0.55.
New customers contributed 30% of YoY revenue growth, up from 25% in the year-ago quarter; existing customers contributed ~70%.
Outlook and guidance
Q4 revenue guidance is $1.19B-$1.20B, representing 25%-26% YoY growth; excluding the largest customer, implied growth is in the low-to-mid 30% range.
Q4 non-GAAP operating income is expected at $280M-$290M; non-GAAP diluted EPS is $0.69-$0.71 on ~379M shares.
FY2026 revenue guidance is $4.515B-$4.525B, or ~32% YoY growth; non-GAAP operating income is $1.095B-$1.105B at a 24% margin.
FY2026 non-GAAP diluted EPS guidance is $2.73-$2.75 on ~375M shares; guidance assumes the largest customer meets its minimum Q4 commitment.
FY2026 guidance includes ~$200M net interest and other income, $30M-$40M cash taxes, a 21% non-GAAP tax rate, and capex plus capitalized software of 3%-4% of revenue; non-GAAP guidance was not reconciled to GAAP.
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Next Datadog earnings date
RBC Global Technology, Internet, Media and Telecommunications Conference18 Nov, 2026
Datadog
Next Datadog earnings date
RBC Global Technology, Internet, Media and Telecommunications Conference18 Nov, 2026
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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