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Datadog
Datadog (DDOG) investor relations material
Datadog Morgan Stanley Technology, Media & Telecom Conference 2026 summary
Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.Morgan Stanley Technology, Media & Telecom Conference 2026 summary3 Mar, 2026
Business performance and growth drivers
Revenue reached $3.4 billion with 28% growth and 22% operating margins, serving over 32,000 customers.
Growth re-accelerated due to increased cloud migration, product expansion, market share gains, and enhanced go-to-market execution.
Larger enterprise deals and broader product adoption are driving higher deal sizes and faster expansion.
About half of customers use all three core product pillars, with consolidation leading to increased customer spend.
Guidance for 2026 targets 19% revenue growth, with the business excluding the largest customer expected to grow over 20%.
Product strategy and innovation
Platform evolved from observability to include security, product analytics, service management, and AI-driven recommendations.
AI is embedded in both the platform and monitoring, aiming to move from observability to actionable insights.
Significant investment in R&D and proprietary AI models leverages unique datasets for competitive advantage.
New products like Bits AI SRE agents and LLM Observability are gaining traction, with over 1,000 customers using Bits AI.
GPU monitoring is in preview, targeting enterprises integrating AI models into production.
Market positioning and competitive landscape
Strong presence among AI-native companies, with 70% of the top 20 as customers and 19 spending over $1 million annually.
Customers prefer the platform over building in-house solutions due to efficiency, ROI, and breadth of features.
Platform scale, integration, and speed of innovation make replication by competitors difficult.
Security business is expanding, with 70% of $1M+ customers using security products and a new specialist sales force being deployed.
Consolidation in the market favors broad platforms over point solutions, with integration and data depth as key differentiators.
Why is Datadog's core platform hard to replicate?
Why deploy a specialist security sales team now?
Why do AI-native firms buy Datadog vs build?
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Next Datadog earnings date
AGM 202621 Apr, 2026
Datadog
Next Datadog earnings date
AGM 202621 Apr, 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
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