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If You Invested in Datadog, Inc. (DDOG)

Services-prepackaged Software · Software - Application · NASDAQ
$1,000 invested 1 Year Ago
$1,142
+14.2% total 14.2% CAGR
Bought on Mar 26, 2025 at $107.97
$1,000 invested 5 Years Ago
$1,536
+53.6% total 9.0% CAGR
Bought on Mar 26, 2021 at $80.29

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$1,000 Investment Over Time

DDOG vs S&P 500

Year-by-Year Returns

DDOG annual performance
Year Start Price End Price Annual Return Cumulative
2019 $37.55 $37.78 +0.6% +0.6%
2020 $36.70 $98.44 +168.2% +162.2%
2021 $91.23 $178.11 +95.2% +374.3%
2022 $163.83 $73.50 -55.1% +95.7%
2023 $72.09 $121.38 +68.4% +223.2%
2024 $115.08 $142.89 +24.2% +280.5%
2025 $143.63 $135.99 -5.3% +262.2%
2026 $133.77 $123.29 -7.8% +228.3%

About Datadog, Inc.

Services-prepackaged Software · NASDAQ

Datadog, Inc. (NASDAQ: DDOG) is described in its public communications as an observability and security platform for cloud applications. The company offers a SaaS platform that integrates and automates multiple monitoring and security capabilities so that customers can gain unified, real-time visibility into their technology environments. According to Datadog, organizations of many sizes and across a wide range of industries use its platform to support digital transformation and cloud migration, improve collaboration across technical and business teams, accelerate application delivery, reduce time to resolve problems, secure applications and infrastructure, understand user behavior, and track key business metrics.

Core platform and capabilities

Datadog states that its SaaS platform brings together infrastructure monitoring, application performance monitoring, log management, user experience monitoring,> and cloud security, among other capabilities, into a single environment. By integrating these data sources, the platform is designed to provide a unified view of customers’ entire technology stack, including cloud infrastructure, applications and user-facing experiences. Datadog also highlights its ability to ingest and analyze large volumes of machine-generated data in real time, enabling customers to monitor systems, investigate incidents and analyze trends.

In earlier descriptions, Datadog has been characterized as a cloud-native company focused on analyzing machine data, with products delivered as software-as-a-service. Its tools enable clients to monitor and analyze their IT infrastructure, from servers to applications and code-level components, and to use machine data across a variety of operational and business applications to support uptime and latency objectives.

Observability for cloud and AI workloads

Datadog’s public announcements emphasize observability for modern cloud environments. The company describes itself as a monitoring and security platform for cloud applications, and highlights support for public cloud providers such as Amazon Web Services and Oracle Cloud Infrastructure. Datadog reports that its platform can unify observability and security telemetry from multiple cloud providers into a single place, giving customers visibility into compute, networking, database performance and other layers of their environments.

Recent announcements also focus on AI and machine learning workloads. Datadog has discussed AI observability and security products, AI-related integrations, and capabilities designed to help customers monitor AI workloads, manage costs and detect misconfigurations. The company has referenced a stack of AI observability and security products and has highlighted integrations related to AI services and GPU monitoring, positioning its platform as a way to manage next-generation workloads at scale.

Security and cloud cost-focused capabilities

Datadog describes several security-focused capabilities within its platform, including cloud security and Cloud SIEM features that bring security telemetry from cloud environments into Datadog. These capabilities are intended to help teams detect and investigate threats across cloud infrastructure and applications. The company has also referenced AI security features intended to detect misconfigurations related to certain AI services.

On the cost side, Datadog has discussed Cloud Cost Management and related offerings that provide visibility into cloud spending and usage. In particular, the company has announced a product called Storage Management, which it says delivers granular visibility into cloud object storage at bucket and prefix levels. According to Datadog, Storage Management is designed to help teams eliminate waste and prevent unexpected cloud object storage spending by providing detailed insights, anomaly detection and targeted optimization recommendations.

Digital experience monitoring and user behavior

Datadog has been recognized in external research for its Digital Experience Monitoring (DEM) capabilities, and the company highlights a DEM suite that includes Synthetic Monitoring and Testing, Real User Monitoring (RUM), Product Analytics, Session Replay and Error Tracking. These tools are described as providing a single source of truth for frontend monitoring data, enabling customers to better understand user activity and troubleshoot frontend issues.

Datadog also references an offering called RUM Without Limits, described as combining detailed insights from complete traffic with filtering tools that help teams uncover trends, detect issues and manage costs. Through these capabilities, Datadog positions its platform as a way for organizations to improve digital experiences, understand user behavior and measure the business impact of changes to applications and services.

AI agents and automation

Datadog has introduced a suite of AI capabilities referred to as Bits AI. Within this suite, the company has launched Bits AI SRE, which it describes as an AI agent that is aware of telemetry, architecture and organizational context. According to Datadog, Bits AI SRE investigates alerts, analyzes runbooks and telemetry, proposes hypothetical root causes, validates its findings and delivers conclusions to collaboration tools. The company presents this as a way to help engineers resolve incidents faster, save engineering time and reduce the impact of production issues on end users and businesses.

Datadog indicates that Bits AI SRE is designed for enterprise scale and notes support for certain regulated workloads, role-based access controls and enterprise contracts with AI partners. The company characterizes this launch as part of a broader AI strategy aimed at intelligent, automated reliability, with AI agents working across monitoring, development and security workflows.

Ecosystem, integrations and partnerships

Datadog frequently emphasizes the breadth of its integrations ecosystem. In its financial communications, the company has highlighted reaching a milestone of about 1,000 integrations on its unified platform. In connection with its collaboration with Amazon Web Services, Datadog has cited more than 1,000 total integrations, including a significant number specific to AWS services, which customers use to monitor their AWS environments.

The company also describes expanded support for Oracle Cloud Infrastructure (OCI), including integrations for GPU Monitoring, Cloud Cost Management and Cloud SIEM. These integrations are presented as helping customers gain full-stack visibility and security across OCI environments, particularly for AI and machine learning workloads. Datadog’s communications further reference collaborations and solution availability through cloud marketplaces and partner programs.

Customer use cases and organizational impact

According to Datadog’s own descriptions, organizations adopt its platform to support several recurring themes: enabling digital transformation and cloud migration, driving collaboration among development, operations, security and business teams, accelerating time to market for applications, reducing time to problem resolution, securing applications and infrastructure, understanding user behavior and tracking key business metrics. Customer comments cited by Datadog describe the platform as providing a unified view of cloud environments, correlating data from multiple systems and helping teams troubleshoot incidents more quickly.

Datadog also notes that its platform is used by organizations of various sizes and across many industries, including sectors such as financial services and the public sector, where it has referenced efforts to meet specific security and compliance expectations. Through these use cases, the company presents its observability and security platform as a central tool for managing complex, cloud-based and digitally driven operations.

Stock listing and regulatory profile

Datadog, Inc. is registered with the U.S. Securities and Exchange Commission and files reports and current reports such as Forms 10-Q, 10-K and 8-K. According to its SEC filings, the company’s Class A common stock, with a stated par value per share, trades on The Nasdaq Stock Market LLC (Nasdaq Global Select Market) under the ticker symbol DDOG. The company provides updates on its financial results, board composition and other material events through these filings and associated press releases.

How Datadog describes its role in the market

Across its public materials, Datadog consistently characterizes itself as a unified observability and security platform for cloud applications. It emphasizes the integration of infrastructure, application, log, user experience and security data, the ability to analyze machine-generated data in real time, and support for modern cloud and AI workloads. The company’s own statements focus on helping customers improve reliability, manage costs, enhance security, and deliver better digital experiences as they adopt and expand cloud-based technologies.

Market Cap
$43.4B
Current Price
$123.29
EPS
$0.31
Revenue
$3.4B
Net Margin
3.1%
View full DDOG overview

Frequently Asked Questions

Datadog, Inc. investment returns

How much would $1,000 invested in Datadog, Inc. be worth today?

If you invested $1,000 in Datadog, Inc. (DDOG) 10 years ago on 2019-09-19, your investment would be worth $3,283 today, representing a +228.3% total return, growing at a compounded rate of 20.0% per year (CAGR).

Has Datadog, Inc. outperformed the S&P 500?

Over the past 10 years, DDOG returned +228.3% compared to +223.2% for the S&P 500, outperforming the benchmark by 5.2 percentage points.

What is Datadog, Inc.'s average annual return?

The compound annual growth rate (CAGR) of DDOG over the past 10 years is 20.0%, growing at a compounded rate each year. Individual years vary significantly — DDOG's best recent year was 2020 (+168.2%) and worst was 2022 (-55.1%).

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