Datadog, Inc.
- Open
- 265.12
- Day high
- 266.91
- Day low
- 254.54
- Prev close
- 264.46
- Volume
- 3.1M
- Mkt cap
- $93.4B
- P/E (TTM)
- 681.7
- EPS (TTM)
- $0.38
- P/B
- 23.4
- P/S
- 25.4
- Yield
- —
- Per share
- —
- ▼Insiders net selling -$285.2M over the last 3 months (0 open-market buys, 185 sales)
- 🏛Institutions accumulating (13F)
Datadog, Inc. (DDOG) is a Technology company listed on NASDAQ. The stock is up 83% over the past year. Over the trailing 3 months, insiders filed 0 open-market buys and 185 sales (SEC Form 4). Drillr has 1 published research article covering DDOG.
Datadog, Inc. (DDOG) financials & analyst ratings
Fundamentals (TTM)
Analyst consensus · 26 analysts
Source: exchange market data + company filings. Figures are trailing-twelve-month or as most recently reported. For informational purposes only — not investment advice.
DDOG earnings date, history & EPS estimates
| Report date | EPS est | EPS actual | Surprise | Revenue | Rev. surprise |
|---|---|---|---|---|---|
| May 7, 2026 | $0.51 | $0.60 | +18.1% | $1.0B | +4.8% |
| Nov 6, 2025 | $0.46 | $0.55 | +20.2% | $886M | +3.9% |
| Aug 7, 2025 | $0.41 | $0.46 | +12.1% | $827M | +4.5% |
| Feb 13, 2025 | $0.44 | $0.49 | +11.4% | $738M | +3.2% |
| Nov 7, 2024 | $0.40 | $0.46 | +15.4% | $690M | +3.8% |
| Aug 8, 2024 | $0.37 | $0.43 | +15.4% | $645M | +2.9% |
| Feb 13, 2024 | $0.43 | $0.44 | +1.5% | $590M | +3.7% |
| May 4, 2023 | $0.24 | $0.28 | +16.7% | $482M | +2.9% |
| Feb 16, 2023 | $0.19 | $0.26 | +36.8% | $469M | +4.3% |
| Nov 3, 2022 | $0.15 | $0.23 | +53.3% | $437M | +5.2% |
| Aug 4, 2022 | $0.14 | $0.24 | +71.4% | $406M | +6.3% |
| May 5, 2022 | $0.11 | $0.24 | +118.2% | $363M | +7.1% |
DDOG insider trading activity (SEC Form 4)
| Date | Insider | Type | Shares | Price |
|---|---|---|---|---|
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 3,911 | $261.53 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 879 | $264.83 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 2,000 | $262.57 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 900 | $258.59 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 4,032 | $259.70 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 6,557 | $260.53 |
| Jul 7, 2026 | Agarwal Amitdirector | Sell | 821 | $265.64 |
| Jul 6, 2026 | Callahan Michael Jamesdirector | Sell | 12,500 | $267.47 |
| Jul 6, 2026 | Phillips Dominicdirector | Grant | 48 | $260.36 |
| Jul 1, 2026 | Callahan Michael Jamesdirector | Sell | 12,500 | $247.47 |
| Jun 29, 2026 | Agarwal Amitdirector | Sell | 1,433 | $218.39 |
| Jun 29, 2026 | Agarwal Amitdirector | Sell | 2,277 | $219.25 |
| Jun 29, 2026 | Agarwal Amitdirector | Sell | 515 | $223.23 |
| Jun 29, 2026 | Agarwal Amitdirector | Sell | 1,000 | $216.93 |
| Jun 29, 2026 | Agarwal Amitdirector | Sell | 600 | $214.52 |
Source: DDOG SEC Form 4 filings, latest Jul 7, 2026. For informational purposes only — not investment advice.
See the full DDOG insider & 13F page →DDOG research & analysis
Datadog, Inc. company profile
Overview
Datadog, Inc. (NASDAQ:DDOG) is a cloud-based monitoring and analytics platform company founded in 2010 and headquartered in New York. The company went public in September 2019 and has grown to become a leading provider of observability solutions for modern cloud infrastructure. Datadog serves approximately 30,000 customers globally, including 45% of Fortune 500 companies, helping organizations monitor, troubleshoot, and optimize their technology stacks in real-time.
Business
Datadog operates in the observability and monitoring sector, providing a comprehensive Software-as-a-Service (SaaS) platform that helps organizations monitor their technology infrastructure and applications. The company's core offering is a unified platform that integrates multiple monitoring capabilities into a single solution. The platform consists of several key product categories. Infrastructure Monitoring represents the largest segment, generating over $1.25 billion in Annual Recurring Revenue (ARR), and tracks the health and performance of servers, containers, and cloud resources. Application Performance Monitoring (APM) products, also exceeding $750 million in ARR, help developers understand how their applications perform and identify bottlenecks or errors. Log Management, another $750+ million ARR product, collects and analyzes log data from various sources to help troubleshoot issues and understand system behavior. Beyond these core pillars, Datadog offers Security Monitoring products that detect threats and vulnerabilities, Database Monitoring that tracks database performance, and newer offerings like LLM Observability for artificial intelligence applications. The company has expanded into adjacent areas including incident management, user experience monitoring, and cloud cost management. Products outside the three main pillars now generate over $200 million in combined ARR. The observability market exists because modern applications are increasingly complex, often running across multiple cloud providers, using microservices architectures, and generating massive amounts of data. Traditional monitoring tools struggle with this complexity, creating a need for unified platforms that can provide comprehensive visibility across an organization's entire technology stack.
Revenue model
Datadog generates revenue primarily through subscription-based pricing tied to usage metrics. Customers pay based on the volume of data they send to the platform, the number of hosts or containers they monitor, and which products they use. This consumption-based model means revenue scales with customer growth and increased technology adoption. The company's customers are primarily technology-focused organizations including software companies, financial services firms, retail companies, and government agencies. These organizations pay for Datadog's services because monitoring and observability are critical operational requirements - system downtime or performance issues can cost millions in lost revenue and customer trust. Datadog's business model benefits from several positive factors. The ongoing cloud migration trend drives demand as organizations move from on-premises infrastructure to cloud environments that require more sophisticated monitoring. The rise of artificial intelligence workloads creates new monitoring needs, with AI-native customers now representing 8.5% of ARR and growing rapidly. Platform consolidation trends work in Datadog's favor as customers prefer unified solutions over managing multiple point tools - 83% of customers now use two or more Datadog products. However, the business faces margin pressures from several sources. Cloud optimization initiatives by customers can reduce usage-based revenue when organizations scale back their infrastructure to control costs. Competition from open-source alternatives and cloud provider native tools can pressure pricing. The company's heavy investment in R&D and sales to maintain competitive positioning also impacts short-term profitability, though this supports long-term market share growth.
Competitive moat
Datadog's competitive moat centers on platform network effects and switching costs, though the strength of this moat is moderate rather than insurmountable. The company benefits from significant switching costs once customers integrate multiple Datadog products into their workflows - with 51% of customers using four or more products, the complexity of replacing the entire stack creates meaningful friction. The platform's data network effects provide some defensive value, as Datadog's monitoring becomes more valuable when it can correlate data across infrastructure, applications, logs, and security in a single interface. The company's extensive integration ecosystem of over 850 integrations creates additional stickiness, as customers would need to rebuild these connections with alternative providers. However, Datadog faces meaningful competitive threats that limit moat strength. Cloud providers like AWS, Google Cloud, and Microsoft Azure offer native monitoring tools that are often free or low-cost, creating pricing pressure especially for basic monitoring needs. Open-source alternatives like Prometheus, Grafana, and Elasticsearch provide viable options for organizations with strong engineering capabilities, though these require significant internal resources to implement and maintain. The observability market remains fragmented with numerous specialized competitors in different product categories. Companies like New Relic, Splunk, and Dynatrace compete directly in various segments, while newer entrants continue to emerge. The relatively low barriers to entry for point solutions in specific monitoring niches means Datadog must continuously innovate to maintain its integrated platform advantage. The company's moat is best described as moderately strong but not impregnable - sufficient to maintain market position and pricing power in the near term, but requiring ongoing investment and innovation to prevent erosion from competitive forces.
Risks & safety
Datadog demonstrates a strong financial position with solid margin of safety characteristics, though valuation remains elevated. • Cash and Liquidity: $1.08 billion in cash and short-term investments with $244 million quarterly free cash flow generation, providing substantial operating cushion • Debt and Solvency: Debt-to-equity ratio of 0.64, manageable debt levels with no immediate solvency concerns given strong cash generation • Profitability: Positive and growing free cash flow margins around 32%, though EBITDA turned slightly negative in Q1 2025 due to increased investments • Valuation Metrics: Current ratio of 2.74 indicates strong short-term liquidity; however, price-to-book ratio of 11.67 suggests elevated valuation relative to tangible assets • Growth vs. Valuation: Revenue growing 25% annually but trading at premium multiples typical of high-growth SaaS companies • Other Considerations: Recurring revenue model provides predictable cash flows; customer concentration in AI-native segment (8.5% of ARR) could create volatility; strong balance sheet supports continued R&D and acquisition investments
Recent development
Over the past few years, Datadog has executed several key strategic initiatives to expand its platform and capture emerging market opportunities. The company has made a significant push into artificial intelligence observability, launching LLM Observability to help customers monitor AI applications and introducing Bits AI for automated incident management. This AI focus has proven successful, with AI-native customers growing from 3% to 8.5% of ARR over the past two years. The company has aggressively expanded its product portfolio through both organic development and strategic acquisitions. Recent acquisitions include Eppo for feature management and Metaplane for data observability, expanding Datadog's capabilities into adjacent markets. New product launches like Flex Logs have achieved rapid adoption, exceeding $50 million in ARR within six quarters, while Database Monitoring approaches $50 million ARR with 60% year-over-year growth. Datadog has also focused on platform consolidation as a key growth driver, successfully increasing multi-product adoption with 51% of customers now using four or more products compared to 47% two years ago. The company has invested heavily in sales and marketing capabilities, particularly in underserved geographical markets and enterprise segments, while expanding its integration ecosystem to over 850 integrations. The company has strengthened its position in security monitoring with enhanced Cloud SIEM capabilities and introduced new service management tools like Datadog OnCall. Infrastructure investments include opening new data centers, including expansion in Australia, to support global growth and compliance requirements including pursuit of FedRAMP High authorization for government customers.
DDOG company profile · for informational purposes only — not investment advice.
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