Datadog (DDOG)
Market Price (4/11/2026): $105.89 | Market Cap: $37.2 BilSector: Information Technology | Industry: Application Software
Datadog (DDOG)
Market Price (4/11/2026): $105.89Market Cap: $37.2 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 28% Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 31%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 27% Valuation becoming less expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is -30% Megatrend and thematic driversMegatrends include Cloud Computing, Cybersecurity, and Artificial Intelligence. Themes include Software as a Service (SaaS), Show more. | Weak multi-year price returns2Y Excs Rtn is -46%, 3Y Excs Rtn is -14% | Not profitable at operating income levelOp Inc LTMOperating Income, Last Twelve Months is -44 Mil, Op Mgn LTMOperating Margin = Operating Income / Revenue Reflects profitability before taxes and before impact of capital structure (interest payments). is -1.3% Expensive valuation multiplesP/EBITPrice/EBIT or Price/(Operating Income) ratio is 268x, P/EPrice/Earnings or Price/(Net Income) is 343x Significant share based compensationSBC/Rev LTMShare Based Compensation / Revenue (Sales), Last Twelve Months (LTM) is 22% 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 -3.6% 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 28% |
| Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 31%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 27% |
| Valuation becoming less expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is -30% |
| Megatrend and thematic driversMegatrends include Cloud Computing, Cybersecurity, and Artificial Intelligence. Themes include Software as a Service (SaaS), Show more. |
| Weak multi-year price returns2Y Excs Rtn is -46%, 3Y Excs Rtn is -14% |
| Not profitable at operating income levelOp Inc LTMOperating Income, Last Twelve Months is -44 Mil, Op Mgn LTMOperating Margin = Operating Income / Revenue Reflects profitability before taxes and before impact of capital structure (interest payments). is -1.3% |
| Expensive valuation multiplesP/EBITPrice/EBIT or Price/(Operating Income) ratio is 268x, P/EPrice/Earnings or Price/(Net Income) is 343x |
| Significant share based compensationSBC/Rev LTMShare Based Compensation / Revenue (Sales), Last Twelve Months (LTM) is 22% |
| 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 -3.6% |
| Key risksDDOG key risks include [1] intense competition from hyperscale cloud providers offering native monitoring tools, Show more. |
Qualitative Assessment
AI Analysis | Feedback
Datadog (DDOG) stock has lost about 25% since 12/31/2025 because of the following key factors:
1. Datadog's lowered fiscal year 2026 revenue growth outlook disappointed investors.
Despite exceeding consensus estimates for Q4 2025 with an EPS of $0.59 (beating by $0.04) and revenue of $953.19 million (up 29.2% year-over-year), the company's guidance for fiscal year 2026 projected revenue growth to decelerate significantly to an 18-20% range. This conservative forecast, following a strong Q4 2025 performance, signaled a slowdown in growth expectations for a stock already trading at a premium, leading to downward pressure.
2. The stock's high valuation coupled with broader "AI disruption fears" in the software sector made it vulnerable.
Datadog was trading at a high valuation, approximately 12 times its annual sales, indicating "skyhigh" expectations. Throughout Q1 2026, the software sector experienced "AI disruption fears" and a "rerating," as investors questioned the long-term robustness of traditional software business models amidst the rapid advancements in AI. This macroeconomic sentiment, impacting high-multiple tech stocks, contributed to Datadog's decline.
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1. Datadog's lowered fiscal year 2026 revenue growth outlook disappointed investors.
Despite exceeding consensus estimates for Q4 2025 with an EPS of $0.59 (beating by $0.04) and revenue of $953.19 million (up 29.2% year-over-year), the company's guidance for fiscal year 2026 projected revenue growth to decelerate significantly to an 18-20% range. This conservative forecast, following a strong Q4 2025 performance, signaled a slowdown in growth expectations for a stock already trading at a premium, leading to downward pressure.
2. The stock's high valuation coupled with broader "AI disruption fears" in the software sector made it vulnerable.
Datadog was trading at a high valuation, approximately 12 times its annual sales, indicating "skyhigh" expectations. Throughout Q1 2026, the software sector experienced "AI disruption fears" and a "rerating," as investors questioned the long-term robustness of traditional software business models amidst the rapid advancements in AI. This macroeconomic sentiment, impacting high-multiple tech stocks, contributed to Datadog's decline.
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Stock Movement Drivers
Fundamental Drivers
The -22.5% change in DDOG stock from 12/31/2025 to 4/10/2026 was primarily driven by a -22.7% change in the company's P/E Multiple.| (LTM values as of) | 12312025 | 4102026 | Change |
|---|---|---|---|
| Stock Price ($) | 135.99 | 105.37 | -22.5% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 3,212 | 3,427 | 6.7% |
| Net Income Margin (%) | 3.3% | 3.1% | -5.4% |
| P/E Multiple | 444.1 | 343.5 | -22.7% |
| Shares Outstanding (Mil) | 349 | 351 | -0.7% |
| Cumulative Contribution | -22.5% |
Market Drivers
12/31/2025 to 4/10/2026| Return | Correlation | |
|---|---|---|
| DDOG | -22.5% | |
| Market (SPY) | -5.4% | 33.7% |
| Sector (XLK) | -0.9% | 40.7% |
Fundamental Drivers
The -26.0% change in DDOG stock from 9/30/2025 to 4/10/2026 was primarily driven by a -23.9% change in the company's Net Income Margin (%).| (LTM values as of) | 9302025 | 4102026 | Change |
|---|---|---|---|
| Stock Price ($) | 142.40 | 105.37 | -26.0% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 3,016 | 3,427 | 13.6% |
| Net Income Margin (%) | 4.1% | 3.1% | -23.9% |
| P/E Multiple | 395.7 | 343.5 | -13.2% |
| Shares Outstanding (Mil) | 346 | 351 | -1.4% |
| Cumulative Contribution | -26.0% |
Market Drivers
9/30/2025 to 4/10/2026| Return | Correlation | |
|---|---|---|
| DDOG | -26.0% | |
| Market (SPY) | -2.9% | 29.1% |
| Sector (XLK) | 1.4% | 34.4% |
Fundamental Drivers
The 6.2% change in DDOG stock from 3/31/2025 to 4/10/2026 was primarily driven by a 86.9% change in the company's P/E Multiple.| (LTM values as of) | 3312025 | 4102026 | Change |
|---|---|---|---|
| Stock Price ($) | 99.21 | 105.37 | 6.2% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 2,684 | 3,427 | 27.7% |
| Net Income Margin (%) | 6.8% | 3.1% | -54.1% |
| P/E Multiple | 183.8 | 343.5 | 86.9% |
| Shares Outstanding (Mil) | 340 | 351 | -3.1% |
| Cumulative Contribution | 6.2% |
Market Drivers
3/31/2025 to 4/10/2026| Return | Correlation | |
|---|---|---|
| DDOG | 6.2% | |
| Market (SPY) | 16.3% | 41.5% |
| Sector (XLK) | 38.8% | 45.8% |
Fundamental Drivers
The 45.0% change in DDOG stock from 3/31/2023 to 4/10/2026 was primarily driven by a 104.6% change in the company's Total Revenues ($ Mil).| (LTM values as of) | 3312023 | 4102026 | Change |
|---|---|---|---|
| Stock Price ($) | 72.66 | 105.37 | 45.0% |
| Change Contribution By: | |||
| Total Revenues ($ Mil) | 1,675 | 3,427 | 104.6% |
| P/S Multiple | 13.8 | 10.8 | -21.6% |
| Shares Outstanding (Mil) | 317 | 351 | -9.6% |
| Cumulative Contribution | 45.0% |
Market Drivers
3/31/2023 to 4/10/2026| Return | Correlation | |
|---|---|---|
| DDOG | 45.0% | |
| Market (SPY) | 63.3% | 41.2% |
| Sector (XLK) | 92.6% | 45.8% |
Price Returns Compared
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | Total [1] | |
|---|---|---|---|---|---|---|---|
| Returns | |||||||
| DDOG Return | 81% | -59% | 65% | 18% | -5% | -20% | 11% |
| Peers Return | 12% | -48% | 85% | 10% | 1% | -32% | -19% |
| S&P 500 Return | 27% | -19% | 24% | 23% | 16% | -0% | 82% |
Monthly Win Rates [3] | |||||||
| DDOG Win Rate | 75% | 25% | 58% | 50% | 50% | 25% | |
| Peers Win Rate | 55% | 32% | 65% | 55% | 43% | 15% | |
| S&P 500 Win Rate | 75% | 42% | 67% | 75% | 67% | 50% | |
Max Drawdowns [4] | |||||||
| DDOG Max Drawdown | -28% | -62% | -15% | -14% | -39% | -25% | |
| Peers Max Drawdown | -21% | -55% | -9% | -27% | -22% | -34% | |
| S&P 500 Max Drawdown | -1% | -25% | -1% | -2% | -15% | -7% | |
[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 4/10/2026 (YTD)
How Low Can It Go
| Event | DDOG | S&P 500 |
|---|---|---|
| 2022 Inflation Shock | ||
| % Loss | -68.1% | -25.4% |
| % Gain to Breakeven | 213.5% | 34.1% |
| Time to Breakeven | 930 days | 464 days |
| 2020 Covid Pandemic | ||
| % Loss | -42.1% | -33.9% |
| % Gain to Breakeven | 72.7% | 51.3% |
| Time to Breakeven | 53 days | 148 days |
Compare to DT, ESTC, NOW, SNOW, CRWD
In The Past
Datadog's stock fell -68.1% during the 2022 Inflation Shock from a high on 11/9/2021. A -68.1% loss requires a 213.5% gain to breakeven.
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About Datadog (DDOG)
Datadog, Inc. provides monitoring and analytics platform for developers, information technology operations teams, and business users in the cloud in North America and internationally. The company's SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, and security monitoring to provide real-time observability of its customers technology stack. Its platform also provides user experience monitoring, network performance monitoring, cloud security, developer-focused observability, and incident management, as well as a range of shared features, such as dashboards, analytics, collaboration tools, and alerting capabilities. The company was incorporated in 2010 and is headquartered in New York, New York.
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.
AI Analysis | Feedback
- 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.
AI Analysis | Feedback
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)
AI Analysis | Feedback
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.
AI Analysis | Feedback
```htmlHere 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.
AI Analysis | Feedback
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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```htmlDatadog (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.
Latest Trefis Analyses
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| Date | Ticker | Company | Category | Trade Strategy | 6M Fwd Rtn | 12M Fwd Rtn | 12M Max DD |
|---|---|---|---|---|---|---|---|
| 03312026 | PANW | Palo Alto Networks | Insider | Insider Buys | Low D/EStrong Insider BuyingCompanies with strong insider buying in the last 1 month, positive operating income and reasonable debt / market cap | 0.0% | 0.0% | 0.0% |
| 03312026 | ALKT | Alkami Technology | Insider | Insider Buys 45DStrong Insider BuyingCompanies with multiple insider buys in the last 45 days | 0.0% | 0.0% | 0.0% |
| 03272026 | DBX | Dropbox | Dip Buy | DB | FCFY OPMDip Buy with High FCF Yield and High MarginBuying dips for companies with high FCF yield and meaningfully high operating margin | 2.6% | 2.6% | 0.0% |
| 03272026 | DLB | Dolby Laboratories | Dip Buy | DB | FCFY OPMDip Buy with High FCF Yield and High MarginBuying dips for companies with high FCF yield and meaningfully high operating margin | 3.5% | 3.5% | 0.0% |
| 03272026 | PTC | PTC | Dip Buy | DB | FCFY OPMDip Buy with High FCF Yield and High MarginBuying dips for companies with high FCF yield and meaningfully high operating margin | 3.5% | 3.5% | 0.0% |
| 12122025 | DDOG | Datadog | Monopoly | MY | Getting CheaperMonopoly-Like with P/S DeclineLarge cap with monopoly-like margins or cash flow generation and getting cheaper based on P/S multiple | -19.1% | -19.1% | -29.7% |
| 02282025 | DDOG | Datadog | Monopoly | MY | Getting CheaperMonopoly-Like with P/S DeclineLarge cap with monopoly-like margins or cash flow generation and getting cheaper based on P/S multiple | 17.3% | -3.9% | -25.4% |
| 05312022 | DDOG | Datadog | Dip Buy | DB | CFO/Rev | Low D/EDip Buy with High Cash Flow MarginsBuying dips for companies with significant cash flows from operations and reasonable debt / market cap | -24.5% | -0.5% | -34.3% |
Research & Analysis
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Peer Comparisons
| Peers to compare with: |
Financials
| Median | |
|---|---|
| Name | |
| Mkt Price | 94.19 |
| Mkt Cap | 39.2 |
| Rev LTM | 4,056 |
| Op Inc LTM | -37 |
| FCF LTM | 1,016 |
| FCF 3Y Avg | 840 |
| CFO LTM | 1,136 |
| CFO 3Y Avg | 935 |
Growth & Margins
| Median | |
|---|---|
| Name | |
| Rev Chg LTM | 21.3% |
| Rev Chg 3Y Avg | 24.7% |
| Rev Chg Q | 22.0% |
| QoQ Delta Rev Chg LTM | 5.1% |
| Op Mgn LTM | -1.5% |
| Op Mgn 3Y Avg | -1.8% |
| QoQ Delta Op Mgn LTM | 0.6% |
| CFO/Rev LTM | 28.4% |
| CFO/Rev 3Y Avg | 29.5% |
| FCF/Rev LTM | 24.9% |
| FCF/Rev 3Y Avg | 26.4% |
Valuation
| Median | |
|---|---|
| Name | |
| Mkt Cap | 39.2 |
| P/S | 7.7 |
| P/EBIT | 38.3 |
| P/E | 9.1 |
| P/CFO | 26.7 |
| Total Yield | 0.1% |
| Dividend Yield | 0.0% |
| FCF Yield 3Y Avg | 1.9% |
| D/E | 0.0 |
| Net D/E | -0.1 |
Returns
| Median | |
|---|---|
| Name | |
| 1M Rtn | -17.7% |
| 3M Rtn | -32.5% |
| 6M Rtn | -41.8% |
| 12M Rtn | -20.8% |
| 3Y Rtn | -12.3% |
| 1M Excs Rtn | -18.3% |
| 3M Excs Rtn | -32.3% |
| 6M Excs Rtn | -42.8% |
| 12M Excs Rtn | -52.2% |
| 3Y Excs Rtn | -83.7% |
Price Behavior
Price Behavior
| Market Price | $105.37 | |
| Market Cap ($ Bil) | 37.0 | |
| First Trading Date | 09/19/2019 | |
| Distance from 52W High | -47.2% | |
| 50 Days | 200 Days | |
| DMA Price | $120.03 | $138.82 |
| DMA Trend | indeterminate | down |
| Distance from DMA | -12.2% | -24.1% |
| 3M | 1YR | |
| Volatility | 66.0% | 53.3% |
| Downside Capture | 1.38 | 0.98 |
| Upside Capture | 273.84 | 150.66 |
| Correlation (SPY) | 33.0% | 30.6% |
DDOG Betas & Captures as of 3/31/2026
[1] Upside and downside betas calculated using positive and negative benchmark daily returns respectively
| 1M | 2M | 3M | 6M | 1Y | 3Y | |
|---|---|---|---|---|---|---|
| Beta | 0.88 | 1.68 | 1.73 | 1.44 | 1.19 | 1.35 |
| Up Beta | 2.92 | 3.30 | 3.47 | 2.74 | 1.24 | 1.18 |
| Down Beta | -0.70 | 1.44 | 0.52 | 0.64 | 1.03 | 1.36 |
| Up Capture | 337% | 206% | 236% | 153% | 155% | 335% |
| Bmk +ve Days | 7 | 16 | 27 | 65 | 139 | 424 |
| Stock +ve Days | 14 | 21 | 29 | 51 | 116 | 382 |
| Down Capture | 39% | 129% | 180% | 151% | 118% | 109% |
| Bmk -ve Days | 12 | 23 | 33 | 58 | 110 | 323 |
| Stock -ve Days | 8 | 21 | 34 | 75 | 135 | 366 |
[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 | 7.3% | 53.2% | 0.31 | - |
| Sector ETF (XLK) | 59.7% | 25.3% | 1.80 | 44.9% |
| Equity (SPY) | 31.2% | 17.3% | 1.47 | 40.1% |
| Gold (GLD) | 60.1% | 27.8% | 1.69 | -5.7% |
| Commodities (DBC) | 29.8% | 16.6% | 1.58 | 7.9% |
| Real Estate (VNQ) | 21.3% | 15.2% | 1.07 | 17.4% |
| Bitcoin (BTCUSD) | -5.7% | 43.7% | -0.01 | 31.5% |
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Based On 5-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with DDOG | |
|---|---|---|---|---|
| DDOG | 2.3% | 55.9% | 0.25 | - |
| Sector ETF (XLK) | 16.5% | 24.7% | 0.60 | 56.3% |
| Equity (SPY) | 11.1% | 17.0% | 0.50 | 52.3% |
| Gold (GLD) | 22.1% | 17.8% | 1.02 | 4.4% |
| Commodities (DBC) | 11.8% | 18.8% | 0.52 | 9.2% |
| Real Estate (VNQ) | 3.7% | 18.8% | 0.10 | 33.8% |
| Bitcoin (BTCUSD) | 4.0% | 56.5% | 0.29 | 28.0% |
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Based On 10-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with DDOG | |
|---|---|---|---|---|
| DDOG | 9.5% | 58.5% | 0.48 | - |
| Sector ETF (XLK) | 21.7% | 24.3% | 0.82 | 52.0% |
| Equity (SPY) | 13.8% | 17.9% | 0.66 | 45.6% |
| Gold (GLD) | 14.2% | 15.9% | 0.74 | 6.8% |
| Commodities (DBC) | 8.6% | 17.6% | 0.41 | 13.1% |
| Real Estate (VNQ) | 5.1% | 20.7% | 0.22 | 29.7% |
| Bitcoin (BTCUSD) | 67.4% | 66.9% | 1.07 | 24.9% |
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Earnings Returns History
Expand for More| Forward Returns | |||
|---|---|---|---|
| Earnings Date | 1D Returns | 5D Returns | 21D Returns |
| 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% |
| ... | |||
| 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 | 28.5% | 31.0% | 50.0% |
| Max Negative | -17.2% | -17.8% | -31.3% |
SEC Filings
Expand for More| Report Date | Filing Date | Filing |
|---|---|---|
| 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 |
Recent Forward Guidance [BETA]
Latest: 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 | |
Prior: Q2 2025 Earnings Reported 8/7/2025
| Forward Guidance | Guidance Change | ||||||
|---|---|---|---|---|---|---|---|
| Metric | Low | Mid | High | % Chg | % Delta | Change | Prior |
| Q3 2025 Revenue | 847.00 Mil | 849.00 Mil | 851.00 Mil | 7.6% | Higher New | Guidance: 789.00 Mil for Q2 2025 | |
| Q3 2025 Non-GAAP Operating Income | 176.00 Mil | 178.00 Mil | 180.00 Mil | 18.7% | Higher New | Guidance: 150.00 Mil for Q2 2025 | |
| Q3 2025 Non-GAAP Net Income Per Share | 0.44 | 0.45 | 0.46 | 9.8% | Higher New | Guidance: 0.41 for Q2 2025 | |
| 2025 Revenue | 3.31 Bil | 3.32 Bil | 3.32 Bil | 2.9% | Raised | Guidance: 3.23 Bil for 2025 | |
| 2025 Non-GAAP Operating Income | 684.00 Mil | 689.00 Mil | 694.00 Mil | 8.5% | Raised | Guidance: 635.00 Mil for 2025 | |
| 2025 Non-GAAP Net Income Per Share | 1.8 | 1.81 | 1.83 | 7.4% | Raised | Guidance: 1.69 for 2025 | |
Insider Activity
Expand for More| # | Owner | Title | Holding | Action | Filing Date | Price | Shares | Transacted Value | Value of Held Shares | Form |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 12312025 | 137.85 | 32,418 | 4,468,788 | 41,555,676 | Form |
| 2 | Pomel, Olivier | Chief Executive Officer | Direct | Sell | 12192025 | 137.93 | 11,195 | 1,544,122 | 71,465,870 | Form |
| 3 | Shah, Shardul | Trust | Sell | 12162025 | 146.94 | 7,916 | 1,163,207 | 51,227,088 | Form | |
| 4 | Walters, Sean Michael | Chief Revenue Officer | Direct | Sell | 12152025 | 149.84 | 9,838 | 1,474,097 | 25,720,124 | Form |
| 5 | Le-Quoc, Alexis | Chief Technology Officer | Direct | Sell | 12082025 | 154.05 | 53,912 | 8,305,201 | 45,514,077 | Form |
External Quote Links
| Y Finance | Barrons |
| TradingView | Morningstar |
| SeekingAlpha | ValueLine |
| Motley Fool | Robinhood |
| CNBC | Etrade |
| MarketWatch | Unusual Whales |
| YCharts | Perplexity Finance |
| FinViz |
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