Key Highlights

● Revenue rose sharply and GAAP operating profit returned

● Full-year outlook was raised

● Fourth-quarter guidance pointed to roughly flat sales

● Shares fell steeply on the update

Datadog, Inc. (NASDAQ:DDOG), one of the software names closely followed among technology stocks, reported that Revenue for the September quarter rose sharply from the prior-year period, while GAAP Net Income climbed well above the year-earlier figure. The New York-based company, which describes itself as an observability and security platform for the AI era, also raised its full-year outlook. Even so, the session ended with a steep decline in the share price, according to market data, which reported that the stock closed sharply lower after the release.

The tension in the report lay between the quarter just completed and the one now under way. Datadog's release showed revenue landing above the range the company had set in August, and non-GAAP Operating Income coming in well above its earlier outlook. Its fourth-quarter revenue guidance, however, was set at a level roughly matching the third quarter, a contrast that drew attention in the coverage that followed. According to market data, management expects fourth-quarter sales to come in "roughly level with the third quarter."

Chief Executive Olivier Pomel framed the quarter around demand, saying in the release that customers were showing "strong adoption" across the platform as they scale digital operations and their use of AI. He added that the company is developing specialized AI models "to help customers manage growing complexity and move towards autonomous operations."

What the Income Statement Showed at Datadog

Revenue rose from the prior-year quarter at a pace of well over a quarter, according to market data copy of the release, marking a sizeable step up in quarterly sales. Gross Profit increased broadly in line with sales, leaving the GAAP gross Margin steady compared with the year-earlier period. That stability matters because it shows the added revenue did not come at the expense of the margin at the top of the income statement.

Below that line, the picture improved more visibly. Datadog swung to a GAAP operating profit from a small operating loss a year earlier, even though total operating expenses increased. GAAP Operating Margin remained in the single digits, while the non-GAAP operating margin was considerably higher, reflecting the adjustments the company makes in its non-GAAP presentation. Non-GAAP operating income rose substantially from the prior-year quarter.

GAAP net income grew to more than triple the prior-year amount, and GAAP Diluted Earnings per Share rose in step with that gain. Non-GAAP diluted earnings per share were also reported for the period. The distance between the GAAP and non-GAAP figures remains wide, so readers comparing the company with its peers typically need to note which measure is being cited.

Cash generation advanced as well. Operating Cash Flow and free cash flow were both up on the prior-year quarter, although free cash flow did not keep pace with revenue, and the free cash flow margin slipped compared with the year-earlier period. Both operating cash flow and free cash flow ran meaningfully above the same stretch of the previous year across the year to date.

Balance Sheet Strength Heading Into Year End

The Balance Sheet expanded during the year. At the end of September, cash, cash equivalents and marketable securities stood at a substantial level, with cash and marketable securities each higher than at the end of December. Total Assets and stockholders' Equity also rose over that period, while total liabilities increased at a slower rate than assets.

Current deferred revenue was modestly above the December level, and the carrying value of the company's convertible senior notes was little changed. In the year-to-date cash flow statement, financing activities produced a net inflow, compared with a sizeable net outflow in the same period a year earlier, and the net outflow from investing activities narrowed. As a result, the net change in cash for the period turned positive after a decline in the prior-year period.

On the call, Chief Financial Officer David Obstler said capital expenditures and capitalized software together were expected to remain a low single-digit share of revenue for the full year, according to a published transcript from market data.

The Largest Customer at the Centre of the Debate

The most scrutinized item from the call involved a single account. According to the transcript, Obstler said the company's largest customer "reduced their usage in the third quarter, while their usage remained above their minimum commitment." He added that fourth-quarter guidance contemplates that customer's revenue at its minimum commitment. Market data described the same arrangement, stating that the forecast assumes the largest customer spends only the minimum required under its contract.

That assumption carries a straightforward mathematical effect. If the customer continues to use the platform above the contract floor, reported revenue would exceed what the guidance builds in for that account. Obstler described such an outcome as "an implicit beat, mathematically," though he declined to quantify how much of the third-quarter outperformance traced to that customer. Market data similarly observed that planning around the floor leaves room for a beat if usage holds at its recent pace.

Management also separated this account from the rest of the Business when discussing the outlook. Excluding the largest customer, the fourth-quarter guidance implied growth considerably faster than the headline rate, according to the transcript. Obstler added that the company intends to guide to contractual minimums for this customer in the future, and that guidance for the following year will come on the year-end call. For observers, this approach effectively isolates one volatile usage stream from the broader Demand picture, although it also leaves the headline outlook looking more subdued.

Early Renewals and the Short-Term Revenue Trade-Off

A second theme concerned contract timing among large customers. Several large customers, including AI companies, renewed early, taking larger commitments in exchange for lower prices. Its article explained that the arrangement yields little immediate sales lift, because customers need to use more of the product to produce the same revenue.

Pomel addressed the same dynamic on the call, saying that early renewals are positive over time but "do create, like, headwind into the short term into the revenue," according to the transcript. Obstler said the renewals come at higher levels than previous commitments, with Volume discounts applied, and Pomel noted that customers often expand their product use when they renew.

Analysts returned to this topic repeatedly in the question period. The transcript shows Gabriela Borges of Goldman Sachs (NYSE:GS) asking how to model quarterly sequential trends for the AI-native cohort given early renewals, and Raimo Lenschow of Barclays asking about the pricing effects. Pomel said the company gets more visibility into the mid-to-long term than into the very short term. Obstler also flagged seasonality, pointing to what he called "the late December effect" as a Factor that typically softens the sequential step between the third and fourth quarters.

Market commentary linked the share price drop to the flat sequential outlook tied to the largest account, along with renewal discounts and the lower projected margin. Its article said the adjusted operating margin implied by fourth-quarter guidance sits several points below the level achieved in the third quarter. The article did not identify a single cause, and its forward-looking views are the author's own opinions rather than company statements.

How the Outlook Changed Since August

Comparing the new guidance with the August release shows how the full-year picture moved. Datadog's second-quarter release, published on its Investor relations site, set the earlier full-year ranges for revenue, non-GAAP operating income and non-GAAP earnings per share. Each of those ranges has now been lifted, with the updated revenue range sitting above the top of the earlier one and the updated profit ranges showing a larger upward shift.

The third-quarter performance against the August outlook helps explain that change. Actual revenue exceeded the top of the range the company had given for the period, and non-GAAP operating income came in well above its earlier range. In other words, much of the upgrade to the full-year outlook reflects results already delivered.

For the fourth quarter, the company guided to revenue that implies slower year-over-year growth than the third-quarter pace, along with non-GAAP operating income below the third-quarter level. Non-GAAP earnings per share guidance also sits below the amount reported for the third quarter. Obstler described the company's philosophy on the call by saying guidance is based on trends observed in recent months, and that it implies conservatism on those growth trends. Datadog has not disclosed what fourth-quarter revenue would look like under other usage scenarios, so any estimate of the gap between guidance and eventual results remains speculative.

Breadth Beyond the AI-Native Cohort

The release reported an increase in customers in its larger annual Recurring Revenue category, compared with a year earlier, and the count also moved up from the level disclosed in the second-quarter release. Pomel said on the call that total customers increased from a year earlier, according to the transcript.

He also pointed to growth outside the AI group. The transcript shows management saying that revenue from non-AI customers accelerated for another straight quarter, with growth considerably faster than the rate seen a year ago. That distinction is relevant to the debate over the largest customer, since it suggests the broader base was gaining speed even as one account pulled back.

Product adoption widened too. The transcript shows Pomel reporting that the share of customers using multiple products rose from a year earlier at each of the thresholds he cited, and that the share of customers using the broadest set of products had doubled. He summed up the trend by saying the company is landing more customers and delivering value across more products through its unified platform. Infrastructure monitoring also passed a new milestone in annual recurring revenue, according to the same transcript.

Retention and growth mix offered further detail. Obstler said trailing net revenue retention remained well above the level at which existing customers would be flat, and gross retention remained high. He also said new customers made a larger contribution to year-over-year revenue growth than a year earlier. Billings and remaining performance obligations both increased from the prior year, though Obstler cautioned that the company continues to view revenue as a better indicator of business trends than either measure.

Scout and the Push Into Specialized Models

On the product side, the release highlighted the launch of Scout, the first specialized model from the company's AI research team, built for investigating production issues. Scout now powers Bits Investigation, and the release said the model, which is in preview, delivers frontier-model performance at a fraction of the inference cost, enabling more frequent investigations.

Pomel said on the call that Scout was built using in-house distributed reinforcement learning infrastructure. He also described Bits AI as the fastest-adopted product in the company's history. According to the transcript, about a third of customers now use at least one AI product, and the proportion is far higher among the larger customers tracked in the release.

Pricing featured in the discussion as well. Pomel said Bits AI uses AI credits priced close to inference cost, passing efficiency gains along to customers. Asked about the model mix by an analyst from Scotiabank, he said the company uses both frontier and open-weight models, and that it post-trains its own. Peter Weed of Bernstein Research also asked how Scout would be priced and monetized, the transcript shows.

The number of AI customers rose from the prior quarter, Pomel said, and a group within that cohort now spends at a high annual level, as described on the call. Monitored GPU devices and customers tracking AI costs through Cloud Cost Management both rose sharply this year. Pomel cautioned that infrastructure monitoring growth was not yet directly tied to GPUs, and said that while AI Training is spreading to more labs, it is not yet a mass market.

Deal Activity and Analyst Recognition

The call included a range of customer examples described without names. The transcript refers to an award from a US federal defense agency following the company's FedRAMP High certification, and to expansions at a leading software company and an online entertainment company. Pomel also cited a home health care software company consolidating several tools onto the platform and large Japanese banks seeking unified visibility across cloud and on-premises systems.

In the AI field, the transcript mentions a top European AI lab adopting CI visibility and test optimization, an expansion with an AI coding company, and a large increase in commitment from the AI division of a large technology company. These descriptions came from management and did not name the parties involved, so they cannot be independently confirmed from the opened sources.

Datadog also cited third-party recognition in its release. It was named a Leader in the Forrester Wave for AIOps Platforms for a second consecutive year, and Gartner's AI Vendor Race report called it the "Company to Beat" among observability platforms. On the call, Pomel described Datadog as the "market share leader in global observability," while noting that its share of the market remains modest.

Security also drew comment. Pomel said the AI Guard product discovers custom agents running across an organization and protects them, and he described demand for agent observability as "crossing the chasm," with customers outside the AI-native group driving that interest.

Questions Left Open After the Report

Several questions remain unresolved after the release. The first is how usage at the largest customer evolves relative to its contract floor. Management has declined to quantify that customer's contribution to the third-quarter outperformance, and the company has signalled that it will continue to plan around the minimum, which means any variance may only be visible after the fact.

The second is how early renewals affect reported growth as the larger commitments work through the year. Management has presented these deals as commitments above earlier levels, while acknowledging a short-term revenue headwind. Karl Keirstead of UBS (NYSE:UBS) also raised a related point on the call, asking how enterprise spending is changing as customers try to control token costs, and Pomel said enterprises are seeking tooling to manage AI spending.

The third concerns margin. Obstler said the company continues to invest in go-to-market and research and development, combining AI with headcount, and that non-GAAP gross margin moves around a familiar range, reflecting platform penetration and engineering projects. Operating expenses grew more slowly than revenue in the quarter, but the fourth-quarter guidance points to a lower operating margin than the third quarter delivered. Further detail on the following year is due with the year-end results, when management said it would issue its next annual guidance.