Key Highlights

● Revenue reached $1.12 billion in the quarter, a 36% increase from a year earlier.

● GAAP Operating Income was only $5 million, versus $257 million on a non-GAAP basis.

● Large customers with $100,000-plus annual Recurring Revenue rose 23% to about 4,720.

● Full-year guidance points to revenue of $4.45 billion to $4.47 billion.

Datadog (NASDAQ:DDOG) reported second-quarter 2026 results on 6 August 2026, and the headline is that revenue reached $1.12 billion, a rise of 36% on the same quarter a year earlier. The figure matters because it shows Demand for observability software continuing to expand at scale, with customers pushing more workloads, and increasingly artificial intelligence applications, onto the platform.

What Datadog does

Datadog sells a cloud-based platform that gathers metrics, logs, traces and security signals from applications and infrastructure, then presents them in one place so engineering teams can find faults and understand performance. The company is generally grouped with infrastructure and observability software, a segment whose spending tends to track the Volume of Cloud Computing activity rather than the number of employees using a product.

In the quarter, the company said general availability had been reached for Bits Code, Bits Chat and Bits Agent Builder, which are its AI-assisted tools. It also announced the Acquisition of Adaptive ML, a startup working on reinforcement learning operations, and launched more than 100 capabilities at its DASH 2026 conference, among them autonomous incident remediation and AI Guard, aimed at protecting AI agents.

Financial performance

Beyond revenue, the release shows a profile that depends heavily on which measure is used. GAAP operating income was only $5 million, a Margin of zero, whereas non-GAAP operating income was $257 million, a 23% margin. The gap reflects items excluded from the adjusted figure, which the release defines. Diluted Earnings per Share were $0.12 on a GAAP basis and $0.65 on a non-GAAP basis.

Cash generation was solid. Operating Cash Flow was $316 million and free cash flow was $279 million. Cash and marketable securities stood at about $5.0 billion at 30 June 2026, giving the company flexibility for acquisitions and product investment.

Customer metrics also moved higher. Datadog counted about 4,720 customers with annual recurring revenue of $100,000 or more, up 23% from about 3,850 a year before. Chief executive Olivier Pomel said that customers are building and deploying with AI and use the platform to observe, secure and act on those solutions.

Outlook and industry context

For the third quarter, management guided to revenue of $1.135 billion to $1.145 billion, non-GAAP operating income of $260 million to $270 million and non-GAAP earnings per share of $0.63 to $0.65. For the full year it guided to revenue of $4.45 billion to $4.47 billion, non-GAAP operating income of $1.01 billion to $1.03 billion and non-GAAP earnings per share of $2.50 to $2.54. These are company expectations, not outcomes, and they can change.

The sector is competitive. Datadog was named a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms for the sixth consecutive year, yet it competes with large cloud providers, established monitoring vendors and open-source tools. Cloud customers also scrutinise software bills, so consumption can slow when they optimise usage.

Risks and uncertainties

Several uncertainties deserve attention. Usage-based pricing means revenue can be sensitive to customer cost control and to the pace of cloud migration. Thin GAAP profitability leaves less cushion if growth slows or if spending on research, sales and acquisitions rises faster than revenue. Integration of acquired businesses such as Adaptive ML carries execution risk, and the commercial return from newly launched AI products has yet to be demonstrated in reported figures.

Tracking Datadog's AI Monetisation Curve

The next checkpoint is the third-quarter report, where observers can compare actual revenue and margins against the guidance ranges above. Other measures worth following include growth in large customers, free cash flow conversion, the take-up of AI-related products, and any further acquisitions funded from the cash balance.