Datadog (DDOG)
Market Price (6/17/2026): $227.0 | Market Cap: $80.2 BilInvestor Relations Sector: Information Technology | Industry: Application Software
Datadog (DDOG)
Market Price (6/17/2026): $227.0Market Cap: $80.2 BilSector: Information TechnologyIndustry: Application Software
Investment Highlights Why It Matters Detailed financial logic regarding cash flow yields vs trend-riding momentum.
Strong revenue growthRev Chg LTMRevenue Change % Last Twelve Months (LTM) is 30% Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 30%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 26% Megatrend and thematic driversMegatrends include Cloud Computing, Cybersecurity, and Artificial Intelligence. Themes include Software as a Service (SaaS), Show more. | Not profitable at operating income levelOp Inc LTMOperating Income, Last Twelve Months is -25 Mil, Op Mgn LTMOperating Margin = Operating Income / Revenue Reflects profitability before taxes and before impact of capital structure (interest payments). is -0.7% Expensive valuation multiplesP/SPrice/Sales ratio is 22x, P/EBITPrice/EBIT or Price/(Operating Income) ratio is 491x, P/CFOPrice/(Cash Flow from Operations). CFO is cash before capital expenditures. is 73x, P/EPrice/Earnings or Price/(Net Income) is 602x Significant share based compensationSBC/Rev LTMShare Based Compensation / Revenue (Sales), Last Twelve Months (LTM) is 21% Valuation getting more expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is 60% Yield minus risk free rate is negativeERPEquity Risk Premium (ERP) = Total Yield - Risk Free Rate, Reflects the premium above risk free assets offered by the investment. is -4.0% Key risksDDOG key risks include [1] intense competition from hyperscale cloud providers offering native monitoring tools, Show more. |
| Strong revenue growthRev Chg LTMRevenue Change % Last Twelve Months (LTM) is 30% |
| Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 30%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 26% |
| Megatrend and thematic driversMegatrends include Cloud Computing, Cybersecurity, and Artificial Intelligence. Themes include Software as a Service (SaaS), Show more. |
| Not profitable at operating income levelOp Inc LTMOperating Income, Last Twelve Months is -25 Mil, Op Mgn LTMOperating Margin = Operating Income / Revenue Reflects profitability before taxes and before impact of capital structure (interest payments). is -0.7% |
| Expensive valuation multiplesP/SPrice/Sales ratio is 22x, P/EBITPrice/EBIT or Price/(Operating Income) ratio is 491x, P/CFOPrice/(Cash Flow from Operations). CFO is cash before capital expenditures. is 73x, P/EPrice/Earnings or Price/(Net Income) is 602x |
| Significant share based compensationSBC/Rev LTMShare Based Compensation / Revenue (Sales), Last Twelve Months (LTM) is 21% |
| Valuation getting more expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is 60% |
| Yield minus risk free rate is negativeERPEquity Risk Premium (ERP) = Total Yield - Risk Free Rate, Reflects the premium above risk free assets offered by the investment. is -4.0% |
| Key risksDDOG key risks include [1] intense competition from hyperscale cloud providers offering native monitoring tools, Show more. |
Qualitative Assessment
AI Analysis | Feedback
Updated on 6/11/2026
Datadog (DDOG) stock has gained about 105% since 2/28/2026 because of the following key factors:
1. Exceptional Fiscal Q1 2026 Financial Results and Elevated Full-Year Guidance.
Datadog announced robust financial performance for its fiscal Q1 2026 (ended March 31, 2026), reporting non-GAAP earnings per share of $0.60, which significantly surpassed analyst estimates of $0.51 to $0.52. Revenue for the quarter reached $1.006 billion, exceeding consensus estimates ranging from $960.12 million to $980.53 million, marking a 32% year-over-year increase and the first time the company's quarterly revenue crossed the $1 billion threshold. Following this strong beat, Datadog raised its full-year fiscal 2026 revenue guidance to between $4.30 billion and $4.34 billion, up from a previous range of $4.06 billion to $4.10 billion, and increased its non-GAAP EPS outlook to $2.36-$2.44 from $2.08-$2.16.
2. Accelerated AI-Powered Product Innovation and Strategic Market Positioning.
At its annual DASH 2026 conference in early June, Datadog unveiled over 100 new AI-powered observability and security capabilities, reinforcing its position as a key enabler for the AI era. Key announcements included significant advancements in its Bits AI suite, which now offers truly autonomous incident management and development workflows, alongside the introduction of AI Guard for enhanced security of AI agents and GPU monitoring tools designed to optimize performance and control costs for scaling AI projects. These innovations directly address the increasing operational complexity and security challenges faced by enterprises deploying and managing AI workloads, making Datadog's platform more integral to modern cloud infrastructure.
Show more
Datadog (DDOG) stock has gained about 105% since 2/28/2026 because of the following key factors:
1. Exceptional Fiscal Q1 2026 Financial Results and Elevated Full-Year Guidance.
Datadog announced robust financial performance for its fiscal Q1 2026 (ended March 31, 2026), reporting non-GAAP earnings per share of $0.60, which significantly surpassed analyst estimates of $0.51 to $0.52. Revenue for the quarter reached $1.006 billion, exceeding consensus estimates ranging from $960.12 million to $980.53 million, marking a 32% year-over-year increase and the first time the company's quarterly revenue crossed the $1 billion threshold. Following this strong beat, Datadog raised its full-year fiscal 2026 revenue guidance to between $4.30 billion and $4.34 billion, up from a previous range of $4.06 billion to $4.10 billion, and increased its non-GAAP EPS outlook to $2.36-$2.44 from $2.08-$2.16.
2. Accelerated AI-Powered Product Innovation and Strategic Market Positioning.
At its annual DASH 2026 conference in early June, Datadog unveiled over 100 new AI-powered observability and security capabilities, reinforcing its position as a key enabler for the AI era. Key announcements included significant advancements in its Bits AI suite, which now offers truly autonomous incident management and development workflows, alongside the introduction of AI Guard for enhanced security of AI agents and GPU monitoring tools designed to optimize performance and control costs for scaling AI projects. These innovations directly address the increasing operational complexity and security challenges faced by enterprises deploying and managing AI workloads, making Datadog's platform more integral to modern cloud infrastructure.
Show more
Updated on 6/11/2026
Datadog (DDOG) stock has gained about 105% since 2/28/2026 because of the following key factors:
1. Exceptional Fiscal Q1 2026 Financial Results and Elevated Full-Year Guidance.
Datadog announced robust financial performance for its fiscal Q1 2026 (ended March 31, 2026), reporting non-GAAP earnings per share of $0.60, which significantly surpassed analyst estimates of $0.51 to $0.52. Revenue for the quarter reached $1.006 billion, exceeding consensus estimates ranging from $960.12 million to $980.53 million, marking a 32% year-over-year increase and the first time the company's quarterly revenue crossed the $1 billion threshold. Following this strong beat, Datadog raised its full-year fiscal 2026 revenue guidance to between $4.30 billion and $4.34 billion, up from a previous range of $4.06 billion to $4.10 billion, and increased its non-GAAP EPS outlook to $2.36-$2.44 from $2.08-$2.16.
2. Accelerated AI-Powered Product Innovation and Strategic Market Positioning.
At its annual DASH 2026 conference in early June, Datadog unveiled over 100 new AI-powered observability and security capabilities, reinforcing its position as a key enabler for the AI era. Key announcements included significant advancements in its Bits AI suite, which now offers truly autonomous incident management and development workflows, alongside the introduction of AI Guard for enhanced security of AI agents and GPU monitoring tools designed to optimize performance and control costs for scaling AI projects. These innovations directly address the increasing operational complexity and security challenges faced by enterprises deploying and managing AI workloads, making Datadog's platform more integral to modern cloud infrastructure.
3. Widespread Analyst Upgrades and Significantly Increased Price Targets.
Following the strong fiscal Q1 2026 earnings report and the strategic product announcements at the DASH 2026 conference, numerous Wall Street analysts reiterated or upgraded their ratings and substantially raised their price targets for Datadog (DDOG). For instance, Bank of America increased its price target to $280, Canadian Imperial Bank of Commerce raised its target from $250 to $280, Benchmark boosted its target to $260 from $230, and Wolfe Research elevated its target to $295. This wave of bullish sentiment led to a strong consensus "Buy" rating for DDOG, with average analyst price targets ranging from approximately $220 to $230, reflecting heightened confidence in the company's growth trajectory and expanding market opportunity in cloud and AI observability.
Show less
Datadog (DDOG) stock has gained about 105% since 2/28/2026 because of the following key factors:
1. Exceptional Fiscal Q1 2026 Financial Results and Elevated Full-Year Guidance.
Datadog announced robust financial performance for its fiscal Q1 2026 (ended March 31, 2026), reporting non-GAAP earnings per share of $0.60, which significantly surpassed analyst estimates of $0.51 to $0.52. Revenue for the quarter reached $1.006 billion, exceeding consensus estimates ranging from $960.12 million to $980.53 million, marking a 32% year-over-year increase and the first time the company's quarterly revenue crossed the $1 billion threshold. Following this strong beat, Datadog raised its full-year fiscal 2026 revenue guidance to between $4.30 billion and $4.34 billion, up from a previous range of $4.06 billion to $4.10 billion, and increased its non-GAAP EPS outlook to $2.36-$2.44 from $2.08-$2.16.
2. Accelerated AI-Powered Product Innovation and Strategic Market Positioning.
At its annual DASH 2026 conference in early June, Datadog unveiled over 100 new AI-powered observability and security capabilities, reinforcing its position as a key enabler for the AI era. Key announcements included significant advancements in its Bits AI suite, which now offers truly autonomous incident management and development workflows, alongside the introduction of AI Guard for enhanced security of AI agents and GPU monitoring tools designed to optimize performance and control costs for scaling AI projects. These innovations directly address the increasing operational complexity and security challenges faced by enterprises deploying and managing AI workloads, making Datadog's platform more integral to modern cloud infrastructure.
3. Widespread Analyst Upgrades and Significantly Increased Price Targets.
Following the strong fiscal Q1 2026 earnings report and the strategic product announcements at the DASH 2026 conference, numerous Wall Street analysts reiterated or upgraded their ratings and substantially raised their price targets for Datadog (DDOG). For instance, Bank of America increased its price target to $280, Canadian Imperial Bank of Commerce raised its target from $250 to $280, Benchmark boosted its target to $260 from $230, and Wolfe Research elevated its target to $295. This wave of bullish sentiment led to a strong consensus "Buy" rating for DDOG, with average analyst price targets ranging from approximately $220 to $230, reflecting heightened confidence in the company's growth trajectory and expanding market opportunity in cloud and AI observability.
Show less
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Stock Movement Drivers
Fundamental Drivers
The 106.4% change in DDOG stock from 2/28/2026 to 6/16/2026 was primarily driven by a 64.9% change in the company's P/E Multiple.| (LTM values as of) | 2282026 | 6162026 | Change |
|---|---|---|---|
| Stock Price ($) | 111.96 | 231.11 | 106.4% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 3,427 | 3,672 | 7.1% |
| Net Income Margin (%) | 3.1% | 3.7% | 17.5% |
| P/E Multiple | 365.0 | 601.8 | 64.9% |
| Shares Outstanding (Mil) | 351 | 353 | -0.6% |
| Cumulative Contribution | 106.4% |
Market Drivers
2/28/2026 to 6/16/2026| Return | Correlation | |
|---|---|---|
| DDOG | 106.4% | |
| Market (SPY) | 9.7% | 14.4% |
| Sector (XLK) | 34.5% | 26.7% |
Fundamental Drivers
The 44.4% change in DDOG stock from 11/30/2025 to 6/16/2026 was primarily driven by a 15.2% change in the company's P/E Multiple.| (LTM values as of) | 11302025 | 6162026 | Change |
|---|---|---|---|
| Stock Price ($) | 160.01 | 231.11 | 44.4% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 3,212 | 3,672 | 14.3% |
| Net Income Margin (%) | 3.3% | 3.7% | 11.1% |
| P/E Multiple | 522.5 | 601.8 | 15.2% |
| Shares Outstanding (Mil) | 349 | 353 | -1.3% |
| Cumulative Contribution | 44.4% |
Market Drivers
11/30/2025 to 6/16/2026| Return | Correlation | |
|---|---|---|
| DDOG | 44.4% | |
| Market (SPY) | 10.4% | 23.0% |
| Sector (XLK) | 30.6% | 34.8% |
Fundamental Drivers
The 96.1% change in DDOG stock from 5/31/2025 to 6/16/2026 was primarily driven by a 146.6% change in the company's P/E Multiple.| (LTM values as of) | 5312025 | 6162026 | Change |
|---|---|---|---|
| Stock Price ($) | 117.88 | 231.11 | 96.1% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 2,835 | 3,672 | 29.5% |
| Net Income Margin (%) | 5.8% | 3.7% | -36.8% |
| P/E Multiple | 244.0 | 601.8 | 146.6% |
| Shares Outstanding (Mil) | 343 | 353 | -2.9% |
| Cumulative Contribution | 96.1% |
Market Drivers
5/31/2025 to 6/16/2026| Return | Correlation | |
|---|---|---|
| DDOG | 96.1% | |
| Market (SPY) | 28.8% | 21.8% |
| Sector (XLK) | 62.4% | 31.5% |
Fundamental Drivers
The 143.5% change in DDOG stock from 5/31/2023 to 6/16/2026 was primarily driven by a 104.7% change in the company's Total Revenues ($ Mil).| (LTM values as of) | 5312023 | 6162026 | Change |
|---|---|---|---|
| Stock Price ($) | 94.91 | 231.11 | 143.5% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 1,794 | 3,672 | 104.7% |
| P/S Multiple | 16.9 | 22.2 | 31.6% |
| Shares Outstanding (Mil) | 319 | 353 | -9.6% |
| Cumulative Contribution | 143.5% |
Market Drivers
5/31/2023 to 6/16/2026| Return | Correlation | |
|---|---|---|
| DDOG | 143.5% | |
| Market (SPY) | 86.6% | 38.8% |
| Sector (XLK) | 131.7% | 44.2% |
Price Returns Compared
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | Total [1] | |
|---|---|---|---|---|---|---|---|
| Returns | |||||||
| DDOG Return | 81% | -59% | 65% | 18% | -5% | 71% | 137% |
| Peers Return | 12% | -48% | 85% | 10% | 1% | 1% | 20% |
| S&P 500 Return | 27% | -19% | 24% | 23% | 16% | 10% | 101% |
Monthly Win Rates [3] | |||||||
| DDOG Win Rate | 75% | 25% | 58% | 50% | 50% | 50% | |
| Peers Win Rate | 55% | 32% | 65% | 55% | 43% | 27% | |
| S&P 500 Win Rate | 75% | 42% | 67% | 75% | 67% | 50% | |
Max Drawdowns [4] | |||||||
| DDOG Max Drawdown | -39% | -62% | -32% | -23% | -43% | -27% | |
| Peers Max Drawdown | -33% | -56% | -20% | -40% | -36% | -38% | |
| S&P 500 Max Drawdown | -5% | -25% | -10% | -8% | -19% | -9% | |
[1] Cumulative total returns since the beginning of 2021
[2] Peers: DT, ESTC, NOW, SNOW, CRWD. See DDOG Returns vs. Peers.
[3] Win Rate = % of calendar months in which monthly returns were positive
[4] Max drawdown represents maximum peak-to-trough decline within a year
[5] 2026 data is for the year up to 6/16/2026 (YTD)
How Low Can It Go
| Event | DDOG | S&P 500 |
|---|---|---|
| 2025 US Tariff Shock | ||
| % Loss | -32.5% | -18.8% |
| % Gain to Breakeven | 48.1% | 23.1% |
| Time to Breakeven | 71 days | 79 days |
| 2024 Yen Carry Trade Unwind | ||
| % Loss | -16.9% | -7.8% |
| % Gain to Breakeven | 20.3% | 8.5% |
| Time to Breakeven | 66 days | 18 days |
| Summer-Fall 2023 Five Percent Yield Shock | ||
| % Loss | -31.3% | -9.5% |
| % Gain to Breakeven | 45.5% | 10.5% |
| Time to Breakeven | 27 days | 24 days |
| 2023 SVB Regional Banking Crisis | ||
| % Loss | -23.8% | -6.7% |
| % Gain to Breakeven | 31.2% | 7.1% |
| Time to Breakeven | 15 days | 31 days |
| 2022 Inflation Shock & Fed Tightening | ||
| % Loss | -53.8% | -24.5% |
| % Gain to Breakeven | 116.4% | 32.4% |
| Time to Breakeven | 782 days | 427 days |
| 2020 COVID-19 Crash | ||
| % Loss | -38.8% | -33.7% |
| % Gain to Breakeven | 63.3% | 50.9% |
| Time to Breakeven | 52 days | 140 days |
In The Past
Datadog's stock fell -32.5% during the 2025 US Tariff Shock. Such a loss loss requires a 48.1% gain to breakeven.
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Asset Allocation
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| Event | DDOG | S&P 500 |
|---|---|---|
| 2025 US Tariff Shock | ||
| % Loss | -32.5% | -18.8% |
| % Gain to Breakeven | 48.1% | 23.1% |
| Time to Breakeven | 71 days | 79 days |
| Summer-Fall 2023 Five Percent Yield Shock | ||
| % Loss | -31.3% | -9.5% |
| % Gain to Breakeven | 45.5% | 10.5% |
| Time to Breakeven | 27 days | 24 days |
| 2023 SVB Regional Banking Crisis | ||
| % Loss | -23.8% | -6.7% |
| % Gain to Breakeven | 31.2% | 7.1% |
| Time to Breakeven | 15 days | 31 days |
| 2022 Inflation Shock & Fed Tightening | ||
| % Loss | -53.8% | -24.5% |
| % Gain to Breakeven | 116.4% | 32.4% |
| Time to Breakeven | 782 days | 427 days |
| 2020 COVID-19 Crash | ||
| % Loss | -38.8% | -33.7% |
| % Gain to Breakeven | 63.3% | 50.9% |
| Time to Breakeven | 52 days | 140 days |
In The Past
Datadog's stock fell -32.5% during the 2025 US Tariff Shock. Such a loss loss requires a 48.1% gain to breakeven.
Preserve Wealth
Limiting losses and compounding gains is essential to preserving wealth.
Asset Allocation
Actively managed asset allocation strategies protect wealth. Learn more.
About Datadog (DDOG)
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Datadog, Inc. (DDOG) provides a comprehensive, cloud-based monitoring and analytics platform, offering real-time observability into an organization's entire technology stack. The company's Software-as-a-Service (SaaS) platform helps developers, IT operations teams, and business users gain insights into the performance, health, and security of their infrastructure and applications, particularly those running in cloud environments.
The core of Datadog's offering is an integrated platform that unifies critical monitoring functions, including infrastructure monitoring, application performance monitoring (APM), log management, and security monitoring. Additionally, the platform provides specialized tools for user experience monitoring, network performance monitoring, cloud security, developer-focused observability, and incident management, all supported by shared features like dashboards, analytics, and alerting capabilities.
Datadog primarily serves businesses and organizations that operate in the cloud, targeting their internal developers, IT operations teams, and various business users. By providing a unified view and automating key monitoring tasks, Datadog enables these teams to proactively manage performance, quickly diagnose issues, and ensure the security of their digital operations across global markets.
```AI Analysis | Feedback
Here are 1-2 brief analogies for Datadog:
- Datadog is like Splunk for monitoring the performance and health of a company's entire software and infrastructure stack.
- Datadog is like a Bloomberg Terminal for IT operations, providing real-time data and analytics on software performance, logs, and security.
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- Infrastructure Monitoring: Provides real-time visibility into the performance and health of IT infrastructure components.
- Application Performance Monitoring (APM): Offers tools to monitor and troubleshoot the performance of applications and services.
- Log Management: Collects, processes, and analyzes log data from various sources for insights and troubleshooting.
- Security Monitoring: Detects and helps respond to security threats across the technology stack.
- User Experience Monitoring: Tracks and analyzes user interactions and experiences with applications and websites.
- Network Performance Monitoring: Monitors and optimizes the performance of network infrastructure.
- Cloud Security: Provides security capabilities specifically designed for cloud environments.
- Developer-Focused Observability: Offers tools and insights tailored for developers to understand their code and systems.
- Incident Management: Helps teams manage and resolve operational incidents efficiently.
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Datadog (symbol: DDOG) primarily sells its monitoring and analytics platform to other companies, rather than individuals. Its customer base consists of a wide range of businesses across various industries, from startups to large enterprises, that require real-time observability of their technology stacks.
While Datadog serves thousands of customers globally, some examples of well-known public companies that have publicly utilized or been highlighted as customers of Datadog's platform include:
- DoorDash (DASH)
- Peloton Interactive (PTON)
- S&P Global (SPGI)
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- Amazon.com, Inc. (AMZN)
- Alphabet Inc. (GOOGL)
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Olivier Pomel, Chief Executive Officer
Olivier Pomel co-founded Datadog in 2010 and has served as CEO since its inception. Before founding Datadog, he was the VP, Technology for Wireless Generation, where he developed data systems for K-12 teachers and expanded the development team until the company's acquisition by News Corp. He previously held software engineering roles at IBM Research and various internet startups. Pomel is an original author of the VLC media player.
David Obstler, Chief Financial Officer
David Obstler joined Datadog as Chief Financial Officer in November 2018, bringing over three decades of operational finance experience, with more than 20 years focused on technology companies. Prior to Datadog, he served as CFO of TravelClick, leading global financial operations. His extensive background includes CFO positions at OpenLink Financial, MSCI Inc., Risk Metrics Group, and Pinnacor. Obstler also held investment banking roles at JPMorgan, Lehman Brothers, and Goldman Sachs. He was appointed to the board of Braze in 2021.
Alexis Lê-Quôc, Chief Technology Officer & Co-founder
Alexis Lê-Quôc co-founded Datadog in 2010 alongside Olivier Pomel. Before Datadog, he was the Director of Operations for Wireless Generation, where he established the team and infrastructure. His professional experience also includes roles at France Telecom R&D and IBM.
Adam Blitzer, Chief Operating Officer
Adam Blitzer's background includes significant roles at Salesforce and Pardot, where he developed expertise in marketing automation and cloud services.
Yanbing Li, Chief Product Officer
Prior to joining Datadog, Yanbing Li served as the Senior Vice President of Engineering at Aurora. Before that, she was the Vice President of Product and Engineering at Google, overseeing Google Cloud Commerce, Cloud Operations, and Service Infrastructure. Li also held multiple executive leadership positions at VMware, including Senior Vice President and General Manager for the Storage and Availability Business Unit.
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Here are the key risks to Datadog's business, listed from most significant to less significant:
- Intense Competition and the Need for Continuous Innovation: Datadog operates in highly competitive markets with numerous established players and new entrants vying for market share. To maintain its competitive position, Datadog must continuously innovate and offer superior products and services. Failure to do so could result in lost customers and reduced market share, negatively impacting the company's business and financial outcomes.
- Cybersecurity Risks: As a provider of cloud-based services, Datadog faces significant cybersecurity threats. Any security breach or incident could severely damage the company's reputation, reduce demand for its products, and lead to substantial legal liabilities. A past incident involving unauthorized access to Datadog's source code repositories highlights these ongoing risks.
- Challenges in Sustaining Profitability and Managing Operational Scale: Despite robust revenue growth, Datadog has a history of operating losses and may struggle to sustain profitability in the future. Rapid expansion can strain operational capabilities, making it difficult for the company to forecast future results and efficiently manage its growing operations while maintaining service quality and innovation.
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The increasing maturity and widespread adoption of open-source observability standards and platforms, particularly **OpenTelemetry**, could pose a clear emerging threat. By standardizing the collection of telemetry data (traces, metrics, logs) across various environments and applications, OpenTelemetry reduces vendor lock-in and allows organizations greater flexibility. This could enable companies to build robust observability stacks using open-source components (e.g., Prometheus for metrics, Grafana for visualization, Loki for logs, Tempo for traces) or to more easily switch between commercial vendors, thereby exerting downward pressure on pricing and reducing the unique value proposition of all-in-one commercial platforms like Datadog.
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Datadog (DDOG) Addressable Market Sizes
Datadog operates within several significant and expanding addressable markets globally. The company's total addressable market (TAM) is projected to reach substantial figures in the coming years, driven by the increasing need for observability, monitoring, and security solutions in complex cloud environments.
- Total Addressable Market (TAM): Datadog's total addressable market, including security, application development, and analytics, is estimated to reach approximately $187 billion by 2029 or 2034. Another estimate places the TAM at $175 billion by 2034, growing at a compound annual growth rate (CAGR) of 17.5%. Current estimates from 2025 place Datadog's TAM at $79 billion, with projections reaching $175 billion by 2034. The cloud observability sector TAM was estimated at US$51 billion as of 2023, with a CAGR of 11% over 2023-2027.
- Observability Platform Market: The global observability platform market was valued at USD 4.1 billion in 2024 and is predicted to grow to about USD 18.1 billion by 2034, at a CAGR of 16%. Other estimates place the global market at USD 3.2 billion in 2024, projected to grow to USD 8.19 billion by 2033 at an 11.0% CAGR, or USD 2.71 billion in 2023, projected to reach USD 5.40 billion by 2030 at a 10.7% CAGR. North America held a dominant market position, capturing more than a 37.9% share in 2024, and leads with approximately 46.4% of the global share in 2025.
- Infrastructure Monitoring Market: The global infrastructure monitoring market size was valued at USD 6.17 billion in 2024 and is poised to grow to USD 15.79 billion by 2033, growing at a CAGR of 11% during the forecast period (2026–2033). Another report estimates the market at USD 5.59 billion in 2024, predicted to increase to USD 15.70 billion by 2034, expanding at a CAGR of 10.88% from 2025 to 2034. North America dominated the market with a 33% revenue share in 2024.
- Application Performance Monitoring (APM) Market: The global Application Performance Monitoring market is estimated at US$9.5 billion in 2024 and is likely to reach a projected US$20.6 billion by 2030, registering a 2024-2030 CAGR of 13.8%. Another source indicates a market size of USD 9.42 billion in 2025, projected to grow to USD 24.14 billion by 2034 with a CAGR of 11.2%. North America leads the global market for Application Performance Monitoring with an estimated 2024 share of 30.2%.
- Log Management Market: The global log management market size was valued at USD 3.27 billion in 2024 and is poised to grow to USD 9.5 billion by 2033, growing at a CAGR of 12.6% during the forecast period (2026–2033). Another outlook estimates revenue from the global log management market to reach US$3.31 billion in 2024, climbing to US$11.03 billion by 2034, expanding at a CAGR of 12.8%. North America is a leading region in the industry, holding a significant log management market share of 38% in 2024.
- Cloud Security Market: The global cloud security market size was valued at USD 51.11 billion in 2025 and is projected to grow to USD 224.16 billion by 2034, registering a CAGR of 17.80% over the forecast period. Other estimates for the global cloud security market size range from USD 35.84 billion in 2024, projected to reach USD 75.26 billion by 2030 with a CAGR of 13.3%, to USD 40.81 billion in 2025, predicted to increase to USD 133.39 billion by 2035 at a CAGR of 12.57%. North America dominated the cloud security market with a market share of 38.00% in 2025.
- User Experience Monitoring (EUEM) Market: The global end user experience monitoring market size was estimated at USD 3.90 billion in 2024 and is anticipated to grow at a CAGR of 15.7% from 2025 to 2030. Another report valued the market at USD 3.88 billion in 2024 and expects it to reach USD 14.94 billion by 2032, growing at a CAGR of 18.44%. North America held a significant revenue share of over 39.0% of the end user experience monitoring industry in 2024.
- Network Performance Monitoring (NPM) Market: The global network performance monitoring market size was valued at USD 4.13 billion in 2025 and is projected to grow to USD 9.52 billion by 2034, exhibiting a CAGR of 9.50% during the forecast period. Another report indicates the market size was USD 2.067 billion in 2025, reaching USD 4.831 billion by 2032 and exhibiting a CAGR of 13.4%. The global network performance monitoring market size is expected to cross USD 12 billion by 2032. North America is anticipated to be the dominant market in 2025.
- Incident Management Market: The global incident and emergency management market size was valued at USD 137.48 billion in 2024 and is predicted to reach around USD 250.01 billion by 2034, expanding at a CAGR of 6.16% from 2025 to 2034. The global incident response market size was valued at USD 26.63 billion in 2025 and is expected to reach USD 358.49 billion by 2033, at a CAGR of 38.40%. North America dominated the incident and emergency management market in 2024.
AI Analysis | Feedback
Here are 3-5 expected drivers of future revenue growth for Datadog (DDOG) over the next 2-3 years:
- Expanding Product Portfolio and Cross-Selling: Datadog continues to broaden its platform by launching new features and capabilities, including security solutions (e.g., unified Cloud Security Management, Cloud SIEM), developer productivity tools (e.g., CI visibility, code-level insights), FinOps add-ons (e.g., cloud cost management), and advanced observability features like Kubernetes Active Remediation and Data Observability. The company's "land-and-expand" strategy is effective, with a high percentage of existing customers adopting multiple products (over 80% use two or more, and adoption of six+ products is rising), leading to higher net revenue retention and increased average revenue per user (ARPU).
- AI-Powered Innovation and Solutions: Datadog is making significant investments in artificial intelligence (AI) and machine learning (ML) to enhance its platform's capabilities, improve automation, and deliver more actionable insights to customers. Key AI-driven initiatives such as Bits AI (for troubleshooting, remediation, and security analysis), LLM Observability, and GPU monitoring are expected to increase platform stickiness and drive the upsell of security and observability modules. The company has seen significant traction in customers' adoption of AI/ML capabilities, with AI-native customer growth significantly outpacing the rest of the business.
- Growth in Enterprise and Public Sector Customer Acquisition and Expansion: Datadog is strategically focusing on acquiring and expanding its presence within larger enterprise and public sector organizations. The number of customers generating over $1 million in annual recurring revenue (ARR) is experiencing significant growth, with 603 enterprise accounts exceeding this threshold in 2025, a 31% increase from the previous year. Datadog is deepening its public-sector and enterprise sales through cloud marketplaces, Global System Integrator (GSI) partnerships, and private-offer integrations to streamline procurement.
- International Expansion: With international clients already contributing approximately 40% of its revenue, Datadog is actively pursuing further expansion in regions like EMEA (Europe, the Middle East, and Africa) and APAC (Asia-Pacific). This involves localized data handling and establishing additional regional presences to meet data residency requirements, providing a multi-year runway for revenue growth from global markets.
AI Analysis | Feedback
Share Repurchases
- Datadog used $28.24 million for stock repurchases in Q4 2025.
Share Issuance
- In December 2024, Datadog issued $1.0 billion of 0% convertible senior notes due 2029.
- In June 2020, Datadog issued $747.5 million of 0.125% convertible senior notes due 2025.
- For the year ended December 31, 2025, Datadog issued 771,355 shares of Class A common stock as consideration in acquisitions.
Outbound Investments
- Datadog acquired Propolis in January 2026, Eppo in May 2025, and Metaplane in April 2025.
- Acquisition of subsidiaries/investments amounted to $46 million in 2024, $12 million in 2023, and $7 million in 2022.
Capital Expenditures
- Capital expenditures amounted to -$135.4 million for the year ended December 31, 2025.
- Capital expenditures were approximately $65 million in 2024, $62 million in 2023, and $96 million in 2022.
- Datadog plans to continue investing heavily in R&D, particularly in AI advancements, and expand go-to-market strategies, having delivered over 400 new features in 2025.
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Peer Comparisons
| Peers to compare with: |
Financials
| Median | |
|---|---|
| Name | |
| Mkt Price | 166.22 |
| Mkt Cap | 82.0 |
| Rev LTM | 4,352 |
| Op Inc LTM | -29 |
| FCF LTM | 1,063 |
| FCF 3Y Avg | 860 |
| CFO LTM | 1,175 |
| CFO 3Y Avg | 959 |
Growth & Margins
| Median | |
|---|---|
| Name | |
| Rev Chg LTM | 22.4% |
| Rev Chg 3Y Avg | 24.7% |
| Rev Chg Q | 23.8% |
| QoQ Delta Rev Chg LTM | 5.5% |
| Op Inc Chg LTM | 22.1% |
| Op Inc Chg 3Y Avg | 29.5% |
| Op Mgn LTM | -1.3% |
| Op Mgn 3Y Avg | -1.4% |
| QoQ Delta Op Mgn LTM | 0.4% |
| CFO/Rev LTM | 29.1% |
| CFO/Rev 3Y Avg | 29.5% |
| FCF/Rev LTM | 26.2% |
| FCF/Rev 3Y Avg | 26.6% |
Price Behavior
Price Behavior
| Market Price | $231.11 | |
| Market Cap ($ Bil) | 81.6 | |
| First Trading Date | 09/19/2019 | |
| Distance from 52W High | -16.7% | |
| 50 Days | 200 Days | |
| DMA Price | $181.73 | $150.55 |
| DMA Trend | up | up |
| Distance from DMA | 27.2% | 53.5% |
| 3M | 1YR | |
| Volatility | 84.2% | 65.4% |
| Downside Capture | -19.76 | 126.26 |
| Upside Capture | 188.91 | 167.86 |
| Correlation (SPY) | 14.8% | 21.9% |
DDOG Betas & Captures as of 5/31/2026
[1] Upside and downside betas calculated using positive and negative benchmark daily returns respectively
| 1M | 2M | 3M | 6M | 1Y | 3Y | |
|---|---|---|---|---|---|---|
| Beta | -3.47 | -1.19 | 0.46 | 1.21 | 1.09 | 1.34 |
| Up Beta | -5.65 | -1.25 | -0.48 | 0.81 | 0.93 | 1.10 |
| Down Beta | -0.33 | -1.24 | 1.70 | 1.59 | 1.12 | 1.45 |
| Up Capture | 380% | 240% | 255% | 198% | 191% | 393% |
| Bmk +ve Days | 13 | 28 | 36 | 67 | 141 | 432 |
| Stock +ve Days | 14 | 27 | 41 | 61 | 120 | 386 |
| Down Capture | -1544% | -833% | -147% | 91% | 92% | 109% |
| Bmk -ve Days | 7 | 13 | 27 | 57 | 109 | 318 |
| Stock -ve Days | 6 | 14 | 22 | 63 | 129 | 362 |
[1] Upside and downside betas calculated using positive and negative benchmark daily returns respectively
Based On 1-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with DDOG | |
|---|---|---|---|---|
| DDOG | 70.3% | 64.1% | 1.07 | - |
| Sector ETF (XLK) | 57.1% | 23.0% | 1.89 | 32.8% |
| Equity (SPY) | 27.2% | 12.4% | 1.66 | 23.6% |
| Gold (GLD) | 25.8% | 27.4% | 0.82 | -3.2% |
| Commodities (DBC) | 23.3% | 18.9% | 0.98 | 2.0% |
| Real Estate (VNQ) | 13.6% | 13.5% | 0.69 | -5.2% |
| Bitcoin (BTCUSD) | -37.7% | 42.4% | -1.00 | 22.9% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 5-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with DDOG | |
|---|---|---|---|---|
| DDOG | 17.4% | 57.8% | 0.50 | - |
| Sector ETF (XLK) | 22.6% | 25.2% | 0.79 | 54.5% |
| Equity (SPY) | 13.8% | 17.1% | 0.63 | 50.1% |
| Gold (GLD) | 17.6% | 18.2% | 0.78 | 3.8% |
| Commodities (DBC) | 7.8% | 19.4% | 0.30 | 8.6% |
| Real Estate (VNQ) | 2.5% | 18.8% | 0.04 | 30.3% |
| Bitcoin (BTCUSD) | 12.1% | 54.2% | 0.42 | 27.2% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 10-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with DDOG | |
|---|---|---|---|---|
| DDOG | 18.5% | 59.7% | 0.67 | - |
| Sector ETF (XLK) | 25.1% | 24.7% | 0.92 | 50.7% |
| Equity (SPY) | 15.4% | 18.0% | 0.73 | 44.0% |
| Gold (GLD) | 12.8% | 16.1% | 0.66 | 6.4% |
| Commodities (DBC) | 6.2% | 18.0% | 0.27 | 12.4% |
| Real Estate (VNQ) | 5.6% | 20.7% | 0.23 | 27.6% |
| Bitcoin (BTCUSD) | 60.7% | 66.8% | 1.00 | 23.9% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Earnings Returns History
Updated 6/16/2026| Forward Returns | |||
|---|---|---|---|
| Earnings Date | 1D Returns | 5D Returns | 21D Returns |
| 5/7/2026 | 31.3% | 42.9% | 62.9% |
| 11/6/2025 | 23.1% | 23.2% | -0.5% |
| 8/7/2025 | -0.4% | -6.0% | -0.6% |
| 5/6/2025 | 0.3% | 7.3% | 13.2% |
| 2/13/2025 | -8.2% | -14.8% | -31.3% |
| 11/7/2024 | 1.1% | 0.1% | 31.4% |
| 8/8/2024 | 5.6% | 5.7% | -0.8% |
| 5/7/2024 | -11.5% | -6.9% | -13.0% |
| ... | |||
| SUMMARY STATS | |||
| # Positive | 12 | 12 | 9 |
| # Negative | 11 | 11 | 14 |
| Median Positive | 11.7% | 11.7% | 27.0% |
| Median Negative | -6.2% | -9.7% | -11.5% |
| Max Positive | 31.3% | 42.9% | 62.9% |
| Max Negative | -17.2% | -17.8% | -31.3% |
| Forward Returns | |||
|---|---|---|---|
| Earnings Date | 1D Returns | 5D Returns | 21D Returns |
| 5/7/2026 | 31.3% | 42.9% | 62.9% |
| 11/6/2025 | 23.1% | 23.2% | -0.5% |
| 8/7/2025 | -0.4% | -6.0% | -0.6% |
| 5/6/2025 | 0.3% | 7.3% | 13.2% |
| 2/13/2025 | -8.2% | -14.8% | -31.3% |
| 11/7/2024 | 1.1% | 0.1% | 31.4% |
| 8/8/2024 | 5.6% | 5.7% | -0.8% |
| 5/7/2024 | -11.5% | -6.9% | -13.0% |
| 2/13/2024 | -2.4% | -5.3% | -8.4% |
| 11/7/2023 | 28.5% | 31.0% | 43.7% |
| 8/8/2023 | -17.2% | -15.5% | -8.1% |
| 5/4/2023 | 14.5% | 30.6% | 50.0% |
| 2/16/2023 | -7.0% | -11.3% | -22.7% |
| 11/3/2022 | 0.7% | -9.7% | 0.3% |
| 8/4/2022 | -1.7% | 4.8% | -13.6% |
| 5/5/2022 | -6.0% | -17.8% | -11.4% |
| 2/10/2022 | 12.3% | 11.8% | -18.3% |
| 11/4/2021 | 11.1% | 14.0% | -3.3% |
| 8/5/2021 | 15.3% | 11.6% | 19.3% |
| 5/6/2021 | 8.3% | 8.5% | 27.0% |
| 2/11/2021 | -4.0% | -10.7% | -25.5% |
| 11/10/2020 | -6.2% | -4.9% | 9.6% |
| 8/6/2020 | -16.4% | -8.4% | -11.6% |
| SUMMARY STATS | |||
| # Positive | 12 | 12 | 9 |
| # Negative | 11 | 11 | 14 |
| Median Positive | 11.7% | 11.7% | 27.0% |
| Median Negative | -6.2% | -9.7% | -11.5% |
| Max Positive | 31.3% | 42.9% | 62.9% |
| Max Negative | -17.2% | -17.8% | -31.3% |
SEC Filings
Expand for More| Report Date | Filing Date | Filing |
|---|---|---|
| 03/31/2026 | 05/07/2026 | 10-Q |
| 12/31/2025 | 02/18/2026 | 10-K |
| 09/30/2025 | 11/07/2025 | 10-Q |
| 06/30/2025 | 08/08/2025 | 10-Q |
| 03/31/2025 | 05/07/2025 | 10-Q |
| 12/31/2024 | 02/20/2025 | 10-K |
| 09/30/2024 | 11/08/2024 | 10-Q |
| 06/30/2024 | 08/09/2024 | 10-Q |
| 03/31/2024 | 05/08/2024 | 10-Q |
| 12/31/2023 | 02/23/2024 | 10-K |
| 09/30/2023 | 11/07/2023 | 10-Q |
| 06/30/2023 | 08/09/2023 | 10-Q |
| 03/31/2023 | 05/05/2023 | 10-Q |
| 12/31/2022 | 02/24/2023 | 10-K |
| 09/30/2022 | 11/04/2022 | 10-Q |
| 06/30/2022 | 08/08/2022 | 10-Q |
| Report Date | Filing Date | Filing |
|---|---|---|
| 03/31/2026 | 05/07/2026 | 10-Q |
| 12/31/2025 | 02/18/2026 | 10-K |
| 09/30/2025 | 11/07/2025 | 10-Q |
| 06/30/2025 | 08/08/2025 | 10-Q |
| 03/31/2025 | 05/07/2025 | 10-Q |
| 12/31/2024 | 02/20/2025 | 10-K |
| 09/30/2024 | 11/08/2024 | 10-Q |
| 06/30/2024 | 08/09/2024 | 10-Q |
| 03/31/2024 | 05/08/2024 | 10-Q |
| 12/31/2023 | 02/23/2024 | 10-K |
| 09/30/2023 | 11/07/2023 | 10-Q |
| 06/30/2023 | 08/09/2023 | 10-Q |
| 03/31/2023 | 05/05/2023 | 10-Q |
| 12/31/2022 | 02/24/2023 | 10-K |
| 09/30/2022 | 11/04/2022 | 10-Q |
| 06/30/2022 | 08/08/2022 | 10-Q |
| 03/31/2022 | 05/06/2022 | 10-Q |
| 12/31/2021 | 02/25/2022 | 10-K |
| 09/30/2021 | 11/05/2021 | 10-Q |
| 06/30/2021 | 08/06/2021 | 10-Q |
| 03/31/2021 | 05/07/2021 | 10-Q |
| 12/31/2020 | 03/01/2021 | 10-K |
| 09/30/2020 | 11/12/2020 | 10-Q |
| 06/30/2020 | 08/10/2020 | 10-Q |
| 03/31/2020 | 05/12/2020 | 10-Q |
| 12/31/2019 | 02/25/2020 | 10-K |
| 09/30/2019 | 11/13/2019 | 10-Q |
| 06/30/2019 | 09/19/2019 | 424B4 |
Recent Forward Guidance
Updated 6/8/2026Latest: Q1 2026 Earnings Reported 5/7/2026
| Forward Guidance | Guidance Change | ||||||
|---|---|---|---|---|---|---|---|
| Metric | Low | Mid | High | % Chg | % Delta | Change | Prior |
| Q2 2026 Revenue | 1.07 Bil | 1.07 Bil | 1.08 Bil | ||||
| Q2 2026 Non-GAAP Operating Income | 225.00 Mil | 230.00 Mil | 235.00 Mil | ||||
| Q2 2026 Non-GAAP Net Income Per Share | 0.57 | 0.58 | 0.59 | ||||
| 2026 Revenue | 4.30 Bil | 4.32 Bil | 4.34 Bil | 27.5% | Higher New | Actual: 3.39 Bil for 2025 | |
| 2026 Non-GAAP Operating Income | 940.00 Mil | 960.00 Mil | 980.00 Mil | 27.0% | Higher New | Actual: 756.00 Mil for 2025 | |
| 2026 Non-GAAP Net Income Per Share | 2.36 | 2.4 | 2.44 | 19.4% | Higher New | Actual: 2.01 for 2025 | |
Prior: Q3 2025 Earnings Reported 11/6/2025
| Forward Guidance | Guidance Change | ||||||
|---|---|---|---|---|---|---|---|
| Metric | Low | Mid | High | % Chg | % Delta | Change | Prior |
| Q4 2025 Revenue | 912.00 Mil | 914.00 Mil | 916.00 Mil | ||||
| Q4 2025 Non-GAAP Operating Income | 216.00 Mil | 218.00 Mil | 220.00 Mil | ||||
| Q4 2025 Non-GAAP Net Income per share | 0.54 | 0.55 | 0.56 | ||||
| 2025 Revenue | 3.39 Bil | 3.39 Bil | 3.39 Bil | 2.1% | Raised | Guidance: 3.32 Bil for 2025 | |
| 2025 Non-GAAP Operating Income | 754.00 Mil | 756.00 Mil | 758.00 Mil | 9.7% | Raised | Guidance: 689.00 Mil for 2025 | |
| 2025 Non-GAAP Net Income per share | 2 | 2.01 | 2.02 | 10.7% | Raised | Guidance: 1.81 for 2025 | |
Insider Activity
Updated 6/17/2026| # | Owner | Title | Holding | Action | Filing Date | Price | Shares | Transacted Value | Value of Held Shares | Form |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 6172026 | 233.91 | 5,371 | 1,256,311 | 29,908,671 | Form |
| 2 | Agarwal, Amit | Trust | Sell | 6162026 | 231.56 | 20,000 | 4,631,193 | 379,758 | Form | |
| 3 | Callahan, Michael James | Trust | Sell | 6162026 | 231.60 | 112,500 | 26,055,155 | 3,473,094 | Form | |
| 4 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6152026 | 231.02 | 11,876 | 2,743,551 | 59,699,263 | Form |
| 5 | Galloreese, David | Chief People Officer | Direct | Sell | 6112026 | 228.90 | 4,013 | 918,590 | 27,969,960 | Form |
| # | Owner | Title | Holding | Action | Filing Date | Price | Shares | Transacted Value | Value of Held Shares | Form |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 6172026 | 233.91 | 5,371 | 1,256,311 | 29,908,671 | Form |
| 2 | Agarwal, Amit | Trust | Sell | 6162026 | 231.56 | 20,000 | 4,631,193 | 379,758 | Form | |
| 3 | Callahan, Michael James | Trust | Sell | 6162026 | 231.60 | 112,500 | 26,055,155 | 3,473,094 | Form | |
| 4 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6152026 | 231.02 | 11,876 | 2,743,551 | 59,699,263 | Form |
| 5 | Galloreese, David | Chief People Officer | Direct | Sell | 6112026 | 228.90 | 4,013 | 918,590 | 27,969,960 | Form |
| 6 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 6102026 | 231.69 | 127,141 | 29,457,514 | 141,968,392 | Form |
| 7 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6102026 | 231.69 | 75,000 | 17,376,592 | 100,689,473 | Form |
| 8 | Cole, Titilope | Direct | Sell | 6082026 | 247.87 | 5,131 | 1,271,844 | 301,415 | Form | |
| 9 | Ittycheria, Dev | Direct | Sell | 6052026 | 248.78 | 120,000 | 29,853,404 | 9,760,819 | Form | |
| 10 | Ittycheria, Dev | LLC | Sell | 6052026 | 248.78 | 18,000 | 4,478,036 | 18,135,798 | Form | |
| 11 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 6042026 | 249.29 | 12,202 | 3,041,813 | 65,754,957 | Form |
| 12 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 6042026 | 267.15 | 26,012 | 6,949,220 | 193,678,658 | Form |
| 13 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6042026 | 267.15 | 13,409 | 3,582,273 | 72,210,766 | Form |
| 14 | Galloreese, David | Chief People Officer | Direct | Sell | 6042026 | 267.15 | 4,711 | 1,258,564 | 33,715,954 | Form |
| 15 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6042026 | 267.15 | 16,323 | 4,360,761 | 136,139,478 | Form |
| 16 | Li, Yanbing | Chief Product Officer | Direct | Sell | 6042026 | 267.15 | 11,070 | 2,957,399 | 73,294,344 | Form |
| 17 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 6042026 | 267.15 | 7,252 | 1,937,404 | 35,594,851 | Form |
| 18 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 6042026 | 267.15 | 13,642 | 3,644,520 | 73,727,401 | Form |
| 19 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 6032026 | 267.15 | 21,506 | 5,745,423 | 136,196,649 | Form |
| 20 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 6032026 | 271.05 | 53,912 | 14,612,581 | 144,009,216 | Form |
| 21 | Jacobson, Matthew | Direct | Sell | 6022026 | 277.46 | 18,020 | 4,999,822 | 162,073,029 | Form | |
| 22 | Jacobson, Matthew | Direct | Sell | 6022026 | 243.02 | 20,574 | 4,999,861 | 146,334,016 | Form | |
| 23 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 5282026 | 223.58 | 84,698 | 18,936,388 | 167,900,865 | Form |
| 24 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 5202026 | 208.04 | 43,224 | 8,992,461 | 110,535,657 | Form |
| 25 | Agarwal, Amit | Trust | Sell | 5132026 | 200.13 | 20,000 | 4,002,637 | 328,216 | Form | |
| 26 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 5132026 | 199.84 | 127,141 | 25,408,082 | 167,003,569 | Form |
| 27 | Richardson, Julie | Direct | Sell | 5112026 | 185.82 | 1,930 | 358,633 | 391,337 | Form | |
| 28 | Richardson, Julie | Direct | Sell | 5112026 | 188.50 | 2,433 | 458,620 | 760,786 | Form | |
| 29 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 5112026 | 188.50 | 7,657 | 1,443,344 | 53,460,485 | Form |
| 30 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 5062026 | 150.00 | 10,806 | 1,620,900 | 79,696,650 | Form |
| 31 | Agarwal, Amit | Trust | Sell | 5062026 | 144.75 | 20,000 | 2,894,938 | 237,385 | Form | |
| 32 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 5062026 | 144.93 | 43,106 | 6,247,534 | 77,005,142 | Form |
| 33 | Agarwal, Amit | Trust | Sell | 4292026 | 131.47 | 20,000 | 2,629,398 | 215,611 | Form | |
| 34 | Agarwal, Amit | Trust | Sell | 4222026 | 125.98 | 20,000 | 2,519,524 | 206,601 | Form | |
| 35 | Agarwal, Amit | Trust | Sell | 4172026 | 120.00 | 20,000 | 2,400,000 | 196,800 | Form | |
| 36 | Shah, Shardul | Trust | Sell | 4172026 | 120.00 | 7,916 | 949,920 | 38,034,360 | Form | |
| 37 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 4132026 | 111.14 | 42,443 | 4,717,074 | 92,876,547 | Form |
| 38 | Agarwal, Amit | Trust | Sell | 4102026 | 122.28 | 20,000 | 2,445,600 | 200,539 | Form | |
| 39 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 4082026 | 116.46 | 32,300 | 3,761,653 | 61,876,398 | Form |
| 40 | Agarwal, Amit | Trust | Sell | 4032026 | 120.53 | 20,000 | 2,410,600 | 197,669 | Form | |
| 41 | Agarwal, Amit | Trust | Sell | 3252026 | 127.36 | 20,000 | 2,547,237 | 208,873 | Form | |
| 42 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 3252026 | 127.75 | 32,418 | 4,141,418 | 55,859,825 | Form |
| 43 | Agarwal, Amit | Trust | Sell | 3182026 | 126.73 | 20,000 | 2,534,673 | 207,843 | Form | |
| 44 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 3182026 | 126.80 | 42,443 | 5,381,599 | 89,368,425 | Form |
| 45 | Shah, Shardul | Trust | Sell | 3172026 | 127.00 | 7,916 | 1,005,344 | 41,258,867 | Form | |
| 46 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 3132026 | 125.68 | 22,330 | 2,806,479 | 29,960,580 | Form |
| 47 | Agarwal, Amit | Trust | Sell | 3112026 | 124.81 | 20,000 | 2,496,118 | 204,682 | Form | |
| 48 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 3042026 | 110.24 | 32,092 | 3,537,903 | 25,391,058 | Form |
| 49 | Li, Yanbing | Chief Product Officer | Direct | Sell | 3042026 | 110.54 | 23,023 | 2,544,866 | 28,076,204 | Form |
| 50 | Obstler, David M | Chief Financial Officer | Direct | Sell | 3042026 | 110.54 | 40,057 | 4,427,737 | 51,578,151 | Form |
| 51 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 3042026 | 110.54 | 17,653 | 1,951,287 | 13,896,659 | Form |
| 52 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 3042026 | 110.54 | 53,541 | 5,918,203 | 48,332,596 | Form |
| 53 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 3042026 | 110.54 | 68,922 | 7,618,355 | 77,908,024 | Form |
| 54 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 3042026 | 110.54 | 32,118 | 3,550,192 | 28,818,257 | Form |
| 55 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 3042026 | 110.54 | 33,429 | 3,695,105 | 29,005,947 | Form |
| 56 | Galloreese, David | Chief People Officer | Direct | Sell | 3042026 | 110.54 | 10,708 | 1,183,617 | 11,665,064 | Form |
| 57 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 2252026 | 104.88 | 21,612 | 2,266,659 | 51,474,723 | Form |
| 58 | Shah, Shardul | Trust | Sell | 2182026 | 126.19 | 7,916 | 998,892 | 41,992,980 | Form | |
| 59 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 2132026 | 126.79 | 43,106 | 5,465,454 | 62,228,783 | Form |
| 60 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 1302026 | 140.99 | 32,418 | 4,570,511 | 42,501,607 | Form |
| 61 | Shah, Shardul | Trust | Sell | 1152026 | 124.89 | 7,916 | 988,660 | 42,551,493 | Form | |
| 62 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 12312025 | 137.85 | 32,418 | 4,468,788 | 41,555,676 | Form |
| 63 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 12192025 | 137.93 | 11,195 | 1,544,122 | 71,465,870 | Form |
| 64 | Shah, Shardul | Trust | Sell | 12162025 | 146.94 | 7,916 | 1,163,207 | 51,227,088 | Form | |
| 65 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 12152025 | 149.84 | 9,838 | 1,474,097 | 25,720,124 | Form |
| 66 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 12092025 | 151.35 | 3,938 | 596,035 | 12,783,867 | Form |
| 67 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 12082025 | 154.05 | 53,912 | 8,305,201 | 45,514,077 | Form |
| 68 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 12042025 | 154.61 | 8,023 | 1,240,413 | 25,540,633 | Form |
| 69 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 12042025 | 154.63 | 32,923 | 5,090,929 | 80,119,623 | Form |
| 70 | Galloreese, David | Chief People Officer | Direct | Sell | 12042025 | 158.60 | 2,554 | 405,061 | 12,279,647 | Form |
| 71 | Li, Yanbing | Chief Product Officer | Direct | Sell | 12042025 | 158.60 | 6,715 | 1,064,989 | 31,623,589 | Form |
| 72 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 12042025 | 158.60 | 8,508 | 1,349,356 | 27,472,432 | Form |
| 73 | Obstler, David M | Chief Financial Officer | Direct | Sell | 12042025 | 158.60 | 12,513 | 1,984,543 | 59,337,726 | Form |
| 74 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 12042025 | 158.60 | 10,530 | 1,670,042 | 28,784,359 | Form |
| 75 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 12042025 | 158.60 | 13,765 | 2,183,108 | 53,712,871 | Form |
| 76 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 12042025 | 158.60 | 15,225 | 2,414,662 | 82,175,117 | Form |
| 77 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 12042025 | 158.60 | 5,018 | 795,847 | 14,020,266 | Form |
| 78 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 11262025 | 158.49 | 43,224 | 6,850,776 | 55,859,409 | Form |
| 79 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 11192025 | 181.18 | 100,754 | 18,254,128 | 96,631,255 | Form |
| 80 | Shah, Shardul | Trust | Sell | 11172025 | 187.23 | 7,916 | 1,482,120 | 66,754,020 | Form | |
| 81 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 11132025 | 197.99 | 53,912 | 10,673,913 | 78,336,013 | Form |
| 82 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 11132025 | 200.14 | 12,859 | Form | |||
| 83 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 11132025 | 200.14 | 18,951 | Form | |||
| 84 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 11132025 | 199.60 | 163,452 | 32,625,573 | 2,566,700 | Form | |
| 85 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 11132025 | 199.60 | 240,854 | 48,075,452 | 3,782,698 | Form | |
| 86 | Callahan, Michael James | Trust | Sell | 11102025 | 187.47 | 12,500 | 2,343,375 | 2,342,625 | Form | |
| 87 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 11052025 | 163.90 | 62,682 | 10,273,557 | 87,417,183 | Form |
| 88 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 10242025 | 154.35 | 11,195 | 1,727,984 | 82,325,496 | Form |
| 89 | Callahan, Michael James | Trust | Sell | 10152025 | 160.55 | 8,333 | 1,337,838 | 2,006,195 | Form | |
| 90 | Shah, Shardul | Trust | Sell | 10152025 | 162.58 | 7,916 | 1,286,955 | 59,250,809 | Form | |
| 91 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 10082025 | 165.02 | 63,939 | 10,551,207 | 88,014,684 | Form |
| 92 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 10082025 | 165.01 | 25,620 | 4,227,449 | 88,007,163 | Form |
| 93 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 10082025 | 154.43 | 32,923 | 5,084,154 | 82,364,124 | Form |
| 94 | Callahan, Michael James | Trust | Sell | 10082025 | 157.60 | 91,667 | 14,446,939 | 1,969,400 | Form | |
| 95 | Agarwal, Amit | Trust | Sell | 10032025 | 150.08 | 45,444 | 6,820,140 | 246,128 | Form | |
| 96 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 10032025 | 150.04 | 2,924 | 438,725 | 28,801,747 | Form |
| 97 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 10032025 | 150.94 | 41,468 | 6,259,029 | 66,243,699 | Form |
| 98 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 9242025 | 137.94 | 11,195 | 1,544,269 | 73,572,885 | Form |
| 99 | Agarwal, Amit | Trust | Sell | 9192025 | 135.23 | 18 | 2,434 | 221,777 | Form | |
| 100 | Agarwal, Amit | Trust | Sell | 9192025 | 134.36 | 10,094 | 1,356,209 | 220,347 | Form | |
| 101 | Agarwal, Amit | Trust | Sell | 9162025 | 134.80 | 33,333 | 4,493,190 | 221,067 | Form | |
| 102 | Agarwal, Amit | Trust | Sell | 9162025 | 138.34 | 44,444 | 6,148,308 | 226,875 | Form | |
| 103 | Shah, Shardul | Trust | Sell | 9162025 | 137.78 | 7,916 | 1,090,673 | 51,304,761 | Form | |
| 104 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 9152025 | 139.62 | 6,821 | 952,344 | 27,209,159 | Form |
| 105 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 9102025 | 135.74 | 32,923 | 4,468,848 | 72,396,074 | Form |
| 106 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 9092025 | 134.72 | 3,958 | 533,219 | 12,585,347 | Form |
| 107 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 9042025 | 132.13 | 7,950 | 1,050,470 | 24,012,566 | Form |
| 108 | Obstler, David M | Chief Financial Officer | Direct | Sell | 9042025 | 133.85 | 12,619 | 1,689,020 | 51,752,231 | Form |
| 109 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 9042025 | 133.85 | 10,622 | 1,421,722 | 26,997,187 | Form |
| 110 | Galloreese, David | Chief People Officer | Direct | Sell | 9042025 | 133.85 | 2,577 | 344,923 | 10,695,840 | Form |
| 111 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 9042025 | 133.85 | 15,357 | 2,055,491 | 71,388,475 | Form |
| 112 | Li, Yanbing | Chief Product Officer | Direct | Sell | 9042025 | 133.85 | 25,010 | 3,347,516 | 27,577,187 | Form |
| 113 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 9042025 | 133.85 | 8,581 | 1,148,543 | 25,387,869 | Form |
| 114 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 9032025 | 133.83 | 55,352 | 7,407,864 | 58,736,822 | Form |
| 115 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 9032025 | 133.85 | 5,142 | 688,244 | 13,033,668 | Form |
| 116 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 9032025 | 139.96 | 12,971 | 1,815,421 | 14,348,559 | Form |
| 117 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 8292025 | 130.00 | 11,195 | 1,455,350 | 71,332,950 | Form |
| 118 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 8282025 | 130.01 | 43,520 | 5,658,142 | 22,922,624 | Form | |
| 119 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 8282025 | 130.01 | 64,128 | 8,337,582 | 33,778,465 | Form | |
| 120 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 8282025 | 126.96 | 232,809 | 29,557,355 | 27,909,672 | Form | |
| 121 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 8282025 | 126.96 | 343,054 | 43,553,918 | 41,126,328 | Form | |
| 122 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 8262025 | 128.60 | 24,243 | 3,117,754 | 58,211,450 | Form | |
| 123 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 8262025 | 128.60 | 35,722 | 4,594,003 | 85,777,396 | Form | |
| 124 | Jacobson, Matthew | ICONIQ Strategic Partners VI, L.P. | Sell | 8262025 | 132.01 | 19,859 | 2,621,589 | 62,953,373 | Form | |
| 125 | Jacobson, Matthew | ICONIQ Strategic Partners VI-B, L.P. | Sell | 8262025 | 132.01 | 29,264 | 3,863,144 | 92,764,685 | Form | |
| 126 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 8122025 | 130.38 | 32,923 | 4,292,337 | 71,538,733 | Form |
| 127 | Cole, Titilope | Direct | Sell | 8122025 | 136.59 | 2,210 | 301,864 | 866,937 | Form | |
| 128 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 8072025 | 134.47 | 41,468 | 5,576,005 | 60,881,692 | Form |
| 129 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 7302025 | 150.82 | 11,195 | 1,688,462 | 82,758,767 | Form |
| 130 | Shah, Shardul | Trust | Sell | 7172025 | 140.80 | 7,924 | 1,115,703 | 53,543,747 | Form | |
| 131 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 7162025 | 139.27 | 41,468 | 5,775,377 | 63,058,547 | Form |
| 132 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 7102025 | 146.05 | 32,924 | 4,808,516 | 80,139,254 | Form |
| 133 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 7082025 | 150.00 | 9,469 | 1,420,350 | 31,848,600 | Form |
| 134 | Obstler, David M | Chief Financial Officer | Direct | Sell | 7082025 | 147.43 | 15,000 | 2,211,450 | 58,864,376 | Form |
| 135 | Obstler, David M | Chief Financial Officer | Direct | Sell | 7022025 | 135.25 | 15,000 | 2,028,750 | 54,001,268 | Form |
| 136 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 6262025 | 131.88 | 100,754 | 13,286,956 | 72,361,912 | Form |
| 137 | Agarwal, Amit | Direct | Sell | 6262025 | 130.87 | 23,058 | 3,017,521 | 4,095,861 | Form | |
| 138 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6232025 | 130.25 | 15,000 | 1,953,750 | 52,004,918 | Form |
| 139 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6182025 | 125.00 | 9,468 | 1,183,500 | 27,724,125 | Form |
| 140 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6182025 | 125.25 | 20,000 | 2,505,000 | 50,008,568 | Form |
| 141 | Shah, Shardul | Trust | Sell | 6182025 | 120.86 | 7,916 | 956,728 | 46,918,456 | Form | |
| 142 | Agarwal, Amit | Direct | Sell | 6132025 | 119.46 | 25,000 | 2,986,558 | 6,493,494 | Form | |
| 143 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6132025 | 119.49 | 4,170 | 498,268 | 27,633,110 | Form |
| 144 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 6112025 | 121.71 | 107,365 | 13,067,746 | 66,785,899 | Form |
| 145 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6062025 | 120.25 | 20,000 | 2,405,000 | 48,012,218 | Form |
| 146 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 6062025 | 119.96 | 127,105 | 15,247,342 | 54,313,551 | Form |
| 147 | Shah, Shardul | Trust | Sell | 6052025 | 120.00 | 23,748 | 2,849,760 | 47,534,520 | Form | |
| 148 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 6042025 | 118.24 | 14,710 | 1,739,324 | 23,442,327 | Form |
| 149 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 6042025 | 116.84 | 15,227 | 1,779,138 | 64,112,409 | Form |
| 150 | Acocella, Kerry | General Counsel and Secretary | Direct | Sell | 6042025 | 116.84 | 5,099 | 595,772 | 13,493,967 | Form |
| 151 | Galloreese, David | Chief People Officer | Direct | Sell | 6042025 | 116.84 | 10,216 | 1,193,648 | 9,637,980 | Form |
| 152 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 6042025 | 116.84 | 11,167 | 1,304,763 | 27,507,993 | Form |
| 153 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 6042025 | 116.84 | 13,766 | 1,608,433 | 52,901,983 | Form |
| 154 | Obstler, David M | Chief Financial Officer | Direct | Sell | 6042025 | 117.40 | 35,016 | 4,111,048 | 46,876,233 | Form |
| 155 | Blitzer, Adam | Chief Operating Officer | Direct | Sell | 6042025 | 116.84 | 15,603 | 1,823,070 | 24,883,511 | Form |
DDOG Trade Sentinel
Stock Conviction
ACCUMULATE (Score 7-8)
CONVICTION RATIONALE
Datadog earns a high conviction score due to its potent combination of accelerating growth and a widening competitive moat. The company is a primary beneficiary of the two most important trends in IT: cloud migration and AI adoption. Leading indicators like 51% RPO growth provide strong visibility that the current momentum is sustainable. While the valuation is high, it appears justified by the superior operational execution and powerful secular tailwinds. The stock is a core holding for a growth-oriented portfolio.
STOCK ARCHETYPE
Primary: 'High-Beta Compounder' (70%), Secondary: 'Transition / Profit Pivot' (30%)Datadog exhibits classic 'High-Beta Compounder' traits with accelerating, premium revenue growth (32% YoY) and a high valuation. The secondary 'Transition' archetype is assigned due to its strong and growing free cash flow generation (29% FCF Margin), indicating a simultaneous focus on achieving profitability at scale.
Looking for high-conviction positions with a better risk/reward profile? See what's currently in the
Trefis High Quality Portfolio.
INVESTMENT THESIS
The primary long thesis is that Datadog is capturing a second secular growth wave from AI-driven workloads, which complements the ongoing cloud migration trend. This is causing an acceleration in revenue growth, visible in both leading (RPO) and lagging (revenue) indicators. This demand, combined with enterprise desire to consolidate tools, allows Datadog to expand its footprint and pricing power within its established customer base.
Mechanism:
Datadog captures value by charging for its monitoring and security platform based on usage (data ingestion, hosts, etc.). The increasing complexity of AI applications requires more intensive monitoring (e.g., GPU performance, model tracing), driving higher consumption. Concurrently, CIOs are replacing multiple niche tools with Datadog's single unified platform, increasing Datadog's share of the IT budget.
Supporting Evidence:
- Revenue growth accelerated to 32% YoY in Q1 2026, up from 29% in the prior quarter.
- Remaining Performance Obligations (RPO), a measure of future contracted revenue, grew 51% YoY in Q1 2026.
- The number of customers with ARR >$100k grew 20.7% YoY, and Net Revenue Retention increased to the 'low 120s%'.
- The company landed seven and eight-figure deals with hyperscale AI labs specifically for new products like GPU Monitoring.
PRIMARY RISK
The primary risk is that major cloud providers (AWS, Azure, GCP) successfully bundle their 'good enough' native observability tools with core cloud services, creating a pricing and integration advantage that slows Datadog's new customer acquisition. This is coupled with the risk that existing customers, facing high data-ingestion costs, aggressively optimize their usage, which would pressure Datadog's 'land-and-expand' model and slow its Net Revenue Retention rate.
Mechanism:
This thesis breaks if hyperscalers' native tools become sufficiently advanced and attractively priced (or free) to convince enterprise customers to forego Datadog's best-in-class unified platform. This would lead to higher churn, lower new logo wins, and slower expansion revenue, causing growth to decelerate faster than the market expects and triggering a significant multiple compression.
Supporting Evidence:
- Hyperscaler native tools are classified as a 'STRUCTURAL' threat in the company's own competitive analysis.
- The 'primary_bear_case' identifies rising observability costs leading to customers filtering data to control spending.
- Datadog's usage-based pricing model can lead to large, unexpected bills, creating a catalyst for customers to explore lower-cost alternatives.
Key KPI Watchlist
| KPI | Threshold | Rationale |
|---|---|---|
| Remaining Performance Obligations (RPO) Growth (YoY) | >40% | This is the best leading indicator of future revenue. As long as it significantly outpaces current revenue growth, the bull thesis of durable acceleration remains intact. |
| Net Revenue Retention (NRR) | Stable or increasing above 120% | Measures the health of the 'expand' motion. A stable or rising NRR proves Datadog is successfully fighting cost-optimization headwinds and cross-selling into its base. |
| Customers with ARR >$100,000 Growth (YoY) | >20% | This signals successful penetration into the enterprise market, which is critical for long-term growth and margin expansion. A slowdown here would be a major red flag. |
Core Investment Debate
AI-Driven Acceleration vs. Hyperscaler Threat
BULL VIEW
Datadog is capturing a second secular growth wave from AI. Strong RPO growth of 51% signals durable revenue acceleration, justifying its premium valuation.
CORE TENSION
Can Datadog's AI-workload adoption and platform consolidation outpace the threat of hyperscalers bundling 'good enough' tools and customers optimizing costs?
PREVAILING SENTIMENT
BEARISH
The Bulls are currently winning based on Q1 2026 results: Revenue growth accelerated to 32% YoY, and leading indicator RPO growth surged to 51%.
BEAR VIEW
Cloud providers (AWS, Azure, GCP) are bundling native tools, pressuring pricing. Aggressive customer cost optimization will slow Net Revenue Retention below market expectations.
Next 6 months: Risks and Catalysts
| Timeline | Event & Metric To Watch |
|---|---|
Early August 2026 | Q2 2026 Earnings Call Watch: Q3 and FY26 guidance. Watch for any deceleration from the >26% YoY growth implied by the last full-year guide. NRR must remain above 120%. |
Early November 2026 | Q3 2026 Earnings Call Watch: FY26 guidance revision and initial FY27 outlook. RPO growth must stay well above revenue growth (>40%) to support the premium multiple. |
Q2/Q3 2026 | Hyperscaler Competitive Actions Watch: Announcements of promotional pricing or free bundling of Google's new 'Agent Platform' or AWS native observability tools for large enterprise customers. |
November 30, 2026 | Catalyst Risk: AWS re:Invent 2026 Watch: AWS CEO keynote announcing a new, fully managed observability service deeply integrated with AI infrastructure (e.g., Bedrock) at a disruptive price point. |
Key Events in Last 6 Months
| Date | Event | Stock Impact |
|---|---|---|
Dec 1, 2025 | Competitor Event (AWS re:Invent) Details: Annual AWS conference where new product announcements for native tools like CloudWatch often create headline risk and competitive pressure for Datadog. [1, 3, 12] | Slight -1.3% pullback $160.01 -> $157.90 |
Feb 10, 2026 | Q4 2025 Earnings Report Details: Reported Q4 revenue of $953M (+29% YoY) and EPS of $0.59, beating estimates. Growth in customers with >$1 million ARR was 31% YoY. [28] | Slight -1.8% pullback $129.67 -> $127.33 |
Feb 23, 2026 | Sector-Wide Tech Selloff Details: Stock experienced a sharp decline amid a broader market rotation out of high-growth software stocks, driven by concerns over valuation and macro headwinds. | Plummeted -11.3% $115.66 -> $102.61 |
Apr 9, 2026 | Competitor Product Announcement (Google Cloud Next) Details: Google announced consolidation of its observability and security tools into a single agent platform, signaling a more aggressive push into Datadog's core market. | Plummeted -6.5% $116.50 -> $108.98 |
May 6, 2026 | FedRAMP High Certification Details: Achieved the highest federal security standard, opening up market for sensitive U.S. government data and workloads, a significant barrier to entry against competitors. [6, 10, 14] | Slight -1.4% pullback $145.73 -> $143.71 |
May 7, 2026 | Q1 2026 Earnings & Guidance Raise Details: Reported accelerating revenue growth of 32% YoY and RPO growth of 51%. Customers with >$100k ARR grew 20.7%. Raised full-year 2026 revenue guidance by over $100M. | Stock surged +31.3% $143.71 -> $188.73 |
Risk Management
Position Sizing
1% - 3%
CONSERVATIVE
Stock is in an Explosive Volatility regime (5.5x S&P) with Spiking near-term fear. The calculated Bearish sentiment, driven by numerous forward risks, mandates a Conservative (1-3%) position despite a widening moat and high visibility.
Diversification Alternatives
CRWD
SECTORA pure-play leader in cybersecurity, another high-priority IT spending area. Offers a similar platform-based, land-and-expand model but with a different primary risk factor.
Core Thesis: CrowdStrike's cloud-native Falcon platform is the standard for endpoint security. Its AI-driven approach and expanding modules create a strong competitive moat in a secular growth market.
IOT
SECTORTaps into a different secular trend: the digitization of physical operations. Less direct competition from hyperscalers compared to Datadog's observability market.
Core Thesis: Samsara's Connected Operations Cloud provides a sticky, high-ROI platform for a large, underserved market. Strong growth in large customers ($100k+ ARR) drives durable revenue.
How Is The Market Pricing DDOG?
Datadog is solidifying its position as the unified observability and security platform for the cloud and AI era, transitioning from a monitoring tool to a mission-critical system of record for complex technology stacks.
Filter all news through the lens of platform consolidation and AI-driven workload adoption.
What will confirm the thesis
Growth in customers with ARR >$100k accelerating above 21% YoY; Net Revenue Retention re-accelerating toward the mid-120s; announcements of new large-scale AI customer wins; evidence of customers consolidating more modules (e.g., security, log management) onto the platform.
What will damage the thesis
Deceleration in large customer additions; Net Revenue Retention falling below 120%; named competitors (Dynatrace, Splunk) winning large enterprise deals citing price or feature gaps; major cloud providers (AWS, Azure, GCP) successfully bundling their native observability tools to displace Datadog.
Noise: Real but irrelevant to thesis
Generic announcements of new product features without customer adoption metrics; quarterly fluctuations in billings growth (management states revenue is a better indicator); individual analyst price target changes without a shift in underlying estimates.
Repricing Catalyst
The adoption of AI workloads is acting as a new secular growth driver alongside cloud migration. In Q1 2026, AI-native customers continued to outpace the rest of the business, and the company now serves 22 AI customers spending over $1M annually. This, combined with accelerating revenue growth (32% YoY in Q1 2026), is driving a re-evaluation of the company's long-term growth trajectory.
What DDOG Makes & Who Pays
TTM figures based on Q1 2026 Earnings Press Release, May 7, 2026
Unified Observability & Security Platform
$4.0B TTM (100% of Total) · 80.2% MarginWhat It Is
A suite of monitoring products including: Infrastructure Monitoring, Application Performance Monitoring (APM), Log Management, Cloud Security Management (CSM), and Real User Monitoring (RUM).
Who Pays & How
Over 33,200 customers, ranging from startups to Fortune 500 companies, pay subscription fees to gain a unified view of their complex cloud environments, which reduces downtime and accelerates troubleshooting. About 4,550 of these customers generate over $100,000 in ARR each, accounting for ~90% of total ARR, indicating deep entrenchment in large enterprises. Switching costs are high due to deep integration, workflow dependencies, and historical data lock-in.
Subscription and usage-based Software-as-a-Service (SaaS). Pricing can be tied to hosts, containers, ingested logs, or number of users.
Competition
Splunk, Dynatrace, New Relic, and native tools from cloud providers (AWS CloudWatch, Google Cloud Operations, Azure Monitor).
Hyperscaler native tools offer deep integration and are often bundled with cloud services, creating a pricing advantage. Point solutions may offer deeper functionality in a specific niche.
Datadog's moat is its unified, easy-to-use platform that consolidates data from over 750 integrations, breaking down silos between Dev, Ops, and Security teams. This single-pane-of-glass approach reduces complexity and improves troubleshooting speed.
DDOG Evolution: Price Return by Era
20102016 · Founding & Infrastructure Focus
Bridging the DevOps Gap Private Company
Founded in 2010 by Olivier Pomel and Alexis Lê-Quôc to reduce friction between developer and operations teams. The company launched its initial cloud infrastructure monitoring service, gaining traction as enterprises began adopting cloud services and needed better visibility than legacy tools could provide.
20172019 · Platform Expansion & IPO
The Three Pillars of Observability +37% on first day of trading (Sep 2019)
Datadog expanded its platform significantly, adding Application Performance Monitoring (APM) in 2017 and Log Management in 2018, unifying the 'three pillars of observability'. This platform approach differentiated it from point solutions and culminated in a successful IPO on September 19, 2019, which raised $648 million.
20202025 · Hyper-Growth & Security Entry
Becoming the System of Record -58.73% (2022), +65.14% (2023)
Following its IPO, Datadog entered a period of rapid growth, expanding its product portfolio into cloud security, digital experience monitoring, and more, through both internal R&D and acquisitions. The company solidified its 'land-and-expand' model, driving multi-product adoption and becoming an essential platform for its rapidly growing enterprise customer base. The stock experienced significant volatility, with a major run-up followed by a correction in 2022.
2026Present · The AI & Consolidation Era
The Second Secular Growth Driver +32.18% (TTM as of May 2026)
Datadog established AI as a second major growth driver alongside cloud migration, launching specific tools like Bits AI and GPU Monitoring. The company crossed the $1 billion quarterly revenue milestone and demonstrated accelerating growth, signaling a new phase of expansion driven by the complexity of AI workloads and customers consolidating more of their tooling onto the Datadog platform.
Market Appears To Be Cautiously Supportive
Price structure is strongly bullish. The regime, trend, and proximity to highs all point towards intact institutional trend. Relative to SPY: Strong 63D outperformance but 'relative strength' momentum is fading, indicating that money rotation may be maturing. Volume and momentum are deeply bearish. The sustained distribution is evident across multiple volume metrics. Earnings history is strongly validating. The market rewarded the print and institutional follow-through confirms thesis re-rating is underway. NOTE: Volume character and price structure are diverging. The structural trend is not confirmed by institutional flow. This divergence typically resolves in the direction of volume, not price.
① Structure
+4
Structural pillar score (-4 to +4). Driven by trend regime, SMA cross events, proximity to 52W high, and relative strength vs SPY.
② Volume / Momentum
-3
Volume/Momentum pillar score (-4 to +4). Driven by institutional footprint score, OBV divergence, and momentum character.
③ Catalyst
+4
Catalyst pillar score (-4 to +4). Driven by earnings day reaction, 20D post-earnings drift, and post-earnings volume character.
Combined Score
5 / 12
1
Price Structure & Trend
Trending Up · Golden Cross
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2
Momentum
Decelerating
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3
Relative Strength vs. SPY
Strong Outperformance
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4
Institutional Footprint & Volume
Neutral / Mixed
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5
Volatility
Normal
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6
Key Price Levels
Range · Vol Falling
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7
Earnings Reaction History
Consistent Reward
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8
How the Verdict Is Derived
Three Pillars
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Industry Resources
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External Quote Links
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| YCharts | Perplexity Finance |
| FinViz |
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Core Cache Last Updated: 6/16/2026