Datadog Q4 Earnings Call Highlights

Datadog (NASDAQ:DDOG) executives highlighted what they called a “very strong” fourth quarter and “really productive” 2025, pointing to accelerating revenue growth, record bookings, and continued demand tied to cloud migration and expanding AI workloads. On the company’s Q4 2025 earnings call, management also detailed broad product momentum across observability, security, and emerging AI-driven capabilities, while issuing its initial outlook for 2026.

Q4 results: revenue growth accelerates and bookings hit a record

For the fourth quarter, Datadog reported revenue of $953 million, up 29% year-over-year and above the high end of guidance. CFO David Obstler said revenue was also up 8% sequentially, driven by “robust sequential usage growth” from existing customers and strong new logo contribution.

Datadog posted $1.63 billion in bookings, up 37% year-over-year, which CEO Olivier Pomel said included “some of the largest deals we’ve ever made.” The company signed 18 deals over $10 million in total contract value (TCV) during the quarter, including two over $100 million. Pomel also cited “an eight-figure land with a leading AI model company.”

On retention, management said churn remained low. Pomel said gross revenue retention was stable in the “mid- to high 90s,” while Obstler said trailing 12-month net revenue retention was about 120%, similar to the prior quarter.

Customer and platform metrics show broader product adoption

Datadog ended Q4 with about 32,700 customers, up from about 30,000 a year earlier. Customers with $100,000 or more in ARR rose to about 4,310 from about 3,610, and management said these customers generate about 90% of ARR.

Pomel emphasized increasing multi-product adoption as evidence that the company’s platform strategy is resonating. At quarter-end:

• 84% of customers used two or more products (up from 83% a year ago)
• 55% used four or more products (up from 50%)
• 33% used six or more products (up from 26%)
• 18% used eight or more products (up from 12%)
• 9% used 10 or more products (up from 6%)

Pomel also said that as of December 2025, 48% of the Fortune 500 are Datadog customers, while the median Datadog ARR among those customers remains under $500,000, which he described as leaving “a very large opportunity” to expand.

Observability pillars and AI initiatives: “AI for Datadog” and “Datadog for AI”

Pomel said Datadog’s three observability pillars continued to grow and cited ARR milestones across the portfolio:

• Infrastructure Monitoring: over $1.6 billion in ARR
• Log Management: over $1 billion in ARR; Flex Logs nearing $100 million in ARR
• APM and DEM suite: crossed $1 billion in ARR; Pomel said core APM accelerated into the “mid-30s%” year-over-year and described it as the company’s fastest growing core pillar

On AI, Pomel framed efforts in two categories. For “AI for Datadog”, he highlighted the general availability launch of Bits AI SRE agent in December and said over 2,000 trial and paying customers ran investigations in the past month. He also discussed progress on Bits AI Dev Agent and Bits AI Security Agent, as well as the Datadog MCP Server, which he said is being used by thousands of customers in preview and saw “explosive growth” with tool calls growing elevenfold in Q4 versus Q3.

For “Datadog for AI”, Pomel said more than 1,000 customers are using the company’s AI observability product and that the number of “brands” has increased 10 times over the past six months. He cited new capabilities added in 2025, including LLM experiments, LLM playground, LLM prompt analysis, and custom “LLM as a judge,” and said Datadog plans to release an AI agents console to monitor usage and adoption of AI agents and coding assistance.

Pomel added that about 5,500 customers use one or more Datadog AI integrations to send data about machine learning, AI, and LLM usage.

Deal highlights: consolidation, multi-product expansion, and AI-related demand

Management repeatedly emphasized consolidation as a driver of large transactions. Pomel described several customer examples, including an eight-figure annualized new logo with a large AI financial model company consolidating more than five tools into Datadog, and a return of a European data company in a nearly seven-figure annualized deal consolidating seven tools and adopting nine Datadog products initially.

Other examples included an eight-figure annualized expansion with a leading e-commerce and digital payments platform standardizing on Datadog APM using OpenTelemetry; Pomel said the customer estimated a 40% reduction in resolution times and has adopted 17 Datadog products. He also cited a Fortune 500 food and beverage retailer expanding logging usage, expecting annual savings “in the $ millions,” and a Latin American financial services customer renewing early while more than quadrupling its annualized commitment after what Pomel described as measurable improvements in cost, efficiency, customer experience, and conversion rates.

Margins, cash flow, and 2026 outlook

Datadog reported non-GAAP gross profit of $776 million and a gross margin of 81.4%. Non-GAAP operating income was $230 million, representing a 24% operating margin. The company ended the quarter with $4.47 billion in cash, cash equivalents, and marketable securities.

Cash flow from operations was $327 million. Free cash flow was $291 million, for a 31% free cash flow margin.

For guidance, Obstler said Datadog’s approach remains based on recent trends with an added layer of conservatism. For Q1 2026, the company expects:

• Revenue of $951 million to $961 million (25% to 26% year-over-year growth)
• Non-GAAP operating income of $195 million to $205 million (21% operating margin)
• Non-GAAP EPS of $0.49 to $0.51 on about 367 million diluted shares

For the full year 2026, Datadog expects:

• Revenue of $4.06 billion to $4.1 billion (18% to 20% year-over-year growth)
• Non-GAAP operating income of $840 million to $880 million (21% operating margin)
• Non-GAAP EPS of $2.08 to $2.16 on about 372 million diluted shares

Obstler said the company’s full-year model includes an assumption that the business excluding its largest customer grows at least 20% during the year, while applying what he described as a “very conservative assumption” for the largest customer given the company’s consumption model.

Additional guidance items included expected net interest and other income of about $140 million in 2026, cash taxes of about $30 million to $40 million, a continued 21% non-GAAP tax rate, and capital expenditures plus capitalized software of 4% to 5% of revenue.

During Q&A, Pomel said he sees AI and agentic development as an “accelerant” for observability due to increased application volume and complexity, and he discussed Datadog’s efforts to serve both humans through UI workflows and agents through tooling such as the MCP server. He also addressed questions on customers building observability in-house, describing it as a small minority of cases and often driven by cultural reasons rather than economics or focus.

Management reiterated plans to continue investing heavily, particularly in R&D, and invited investors to the company’s Investor Day in New York later that week.

About Datadog (NASDAQ:DDOG)

Datadog (NASDAQ: DDOG) is a cloud-based monitoring and observability platform that helps organizations monitor, troubleshoot and secure their applications and infrastructure at scale. Its software-as-a-service offering collects and analyzes metrics, traces and logs from servers, containers, cloud services and applications to provide real-time visibility into system performance and health. Datadog’s platform is widely used by engineering, operations and security teams to reduce downtime, accelerate incident response and improve application reliability.

The company’s product suite includes infrastructure monitoring, application performance monitoring (APM), log management, real user monitoring (RUM), synthetic monitoring and network performance monitoring, along with security-focused products such as security monitoring and cloud SIEM.