Takeaways by Saasverse AI
- $886M Revenue (+28%) | $0.55 Adjusted EPS (+19%) | Free Cash Flow: $214M | Non-GAAP Operating Margin: 23%.
- AI Business Revenue Share Doubled to 12% | Over 500 AI-native Customers, 15 Spending $1M+ Annually | 1,000+ Product Integrations.
- Stock Jumped 23.13% to $190.82 | Raised FY Guidance to $3.386-$3.390B Revenue | Expanded OCI Support, Pioneering GPU Monitoring.
Datadog, the cloud monitoring and observability platform leader, delivered an outstanding performance in Q3 2025, with revenue surging 28% year-over-year to $886 million, handily exceeding market expectations. The company reported adjusted earnings per share (EPS) of $0.55, beating the consensus estimate of $0.46, while free cash flow reached $214 million. In response to the stellar results, Datadog raised its full-year revenue guidance to $3.386-$3.390 billion and adjusted EPS to $2.00-$2.02. The market reacted enthusiastically, sending Datadog shares soaring by 23.13% to $190.82, making it the top performer in the S&P 500 for the day.
Datadog’s success this quarter underscores its strategic focus on AI-driven innovation and enterprise-grade solutions. The company has aggressively expanded its AI capabilities, launching a suite of full-stack AI observability and security products, including the Bits AI assistant for developers, SREs, and security teams, as well as the Datadog MCP Server and its proprietary TOTO time-series foundational model. These initiatives have strengthened Datadog’s value proposition, particularly among large-scale enterprise customers, and solidified its leadership in the observability market with over 1,000 product integrations.
AI has emerged as a key growth driver for Datadog. The company reported that revenue from AI-native customers doubled from 6% to 12% of total revenue year-over-year. Over 500 AI-centric companies now leverage Datadog’s platform, with 15 of them contributing over $1 million in annual spending. Total customer count rose to 32,000, with 4,060 customers generating annual recurring revenue (ARR) of $100,000 or more, a 16% increase from the prior year. Notably, 84% of customers now use two or more Datadog products, while 54% leverage four or more, reflecting strong platform adoption.
In terms of product innovation, Datadog made headlines by expanding its support for Oracle Cloud Infrastructure (OCI). The platform introduced GPU monitoring, cloud cost management, and cloud SIEM capabilities, making Datadog one of the first observability providers to offer GPU monitoring for OCI. While GPU monitoring has not yet materially contributed to revenue, it represents a significant growth opportunity as enterprises adopt AI workloads at scale.
Operationally, Datadog demonstrated impressive efficiency, with a gross margin of 81.2% and a non-GAAP operating margin of 23%, highlighting the scalability of its business model. The company continues to benefit from the broader industry trend of increased cloud spending and digital transformation, as evidenced by strong market data from competitors like MongoDB.
Looking ahead, Datadog projects Q4 2025 revenue in the range of $912-$916 million, reflecting a 24% year-over-year growth at the midpoint, albeit with a slightly conservative outlook in the face of macroeconomic uncertainties. Nevertheless, the company’s robust product portfolio, increasing share of AI-related revenue, and expanding enterprise customer base position it well for sustained growth. With its stock already up over 33% year-to-date, Datadog remains a standout performer in the SaaS and cloud ecosystem, exemplifying how AI innovation can unlock new avenues for growth and profitability.
Saasverse Insights
Datadog’s Q3 performance highlights the transformative impact of AI on cloud observability solutions. The doubling of AI-related revenue underscores the growing importance of AI-native customers, and its pioneering GPU monitoring capabilities position the company to capture emerging opportunities in AI workloads. However, given its high valuation and reliance on enterprise spending, Datadog must navigate potential macroeconomic headwinds carefully. Investors should watch for further advancements in AI and product adoption metrics as key indicators of long-term growth potential.