Datadog guides fourth-quarter revenue of $1.19 billion to $1.20 billion, according to the third-quarter release it filed on 4 November. Against $953.2 million in the fourth quarter of 2025, that is growth of 24.8% to 25.9%, by our arithmetic, after 35% in the third quarter.
The range sits around third-quarter revenue of $1.197 billion: from 0.6% below it to 0.2% above it, by our arithmetic. Free cash flow in the third quarter was $251 million.
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The key insight: Datadog’s fourth-quarter range of $1.19 billion to $1.20 billion implies growth of 24.8% to 25.9% against $953.2 million a year earlier, after 35.2% in the third quarter, and sits between 0.6% below and 0.2% above third-quarter revenue, by our arithmetic.
Revenue was $1.20 billion, up 35%. GAAP operating income was $75 million, a 6% margin, and non-GAAP operating income was $334 million, a 28% margin. Operating cash flow was $290 million and cash, cash equivalents and marketable securities were $5.2 billion.
Datadog had about 4,860 customers with ARR of $100,000 or more, up 20% from about 4,060 a year earlier. GAAP net income per diluted share was $0.32 and non-GAAP was $0.81.
Datadog quarterly revenue from the first quarter of 2025 to the third quarter of 2026, and the fourth-quarter 2026 guidance range of $1.19 billion to $1.20 billion, with growth against a year earlier. Source: Datadog Q3 2026 release (Form 8-K Exhibit 99.1) and Forms 10-Q and 10-K via SEC XBRL. Fourth-quarter 2025 revenue and growth rates are our arithmetic.
Comments: ๐ธ โDatadog delivered a strong third quarter, with 35% year-over-year revenuegrowth, $290 million in operating cash flow, and $251 million in free cash flow.โ
๐ธ โWe are innovating rapidly, including developing specialized AI models through our AI Research team, to help customers manage growing complexity and move towards autonomous operations.โ
Wall St Engine’s results card, posted at 12:03Z, lists Datadog’s third-quarter figures and guidance against consensus estimates and the Scout 1.0 launch. We use it only for the estimates; Datadog’s financial figures come from the release and filings.
DataDog CEO: “…we executed a strong Q3. We saw strength across our business, including across our product lines and across our diverse customer base”
The Transcript’s post at 14:41Z quotes a line it attributes to Datadog’s CEO on the earnings call, calling it a strong Q3, and puts the stock’s fall at 13% that day. We have not read the call transcript ourselves.
How the Fourth-Quarter Range Compares
Datadog’s 10-K puts 2025 revenue at $3.427 billion; minus the first nine months, $2.474 billion, the fourth quarter of 2025 was $953.2 million, by our arithmetic. That quarter was 7.6% above the third quarter of 2025, and the fourth quarter of 2024 was 6.9% above its third quarter, by the same method.
Growth in 2026 ran at 32.2% in the first quarter, 35.6% in the second and 35.2% in the third, by our arithmetic from the filings. The fourth-quarter range implies about 25%.
The full-year guidance of $4.515 billion to $4.525 billion, minus nine-month revenue of $3.325 billion, leaves $1.190 billion to $1.200 billion, the same as the quarterly range, by our arithmetic. Guided non-GAAP operating income of $280 million to $290 million is a 23.5% to 24.2% margin, against 27.9% in the third quarter, by the same method.
The release does not say why the fourth-quarter range sits at the third quarter’s level.
The AI Line
Chief executive Olivier Pomel said: “We are seeing strong adoption across our platform as customers scale their digital operations and use of AI”. He added that Datadog is “developing specialized AI models through our AI Research team, to help customers manage growing complexity and move towards autonomous operations”.
The release says Scout 1.0, its first specialized model, “now powers Bits Investigation and achieves frontier-model performance at a fraction of the inference cost”. The release gives no share of revenue from AI-native customers. Research and development was 41.1% of third-quarter revenue, by our arithmetic.
Against the Consensus
Against the consensus estimates cited by Wall St Engine, revenue of $1.20 billion compared with $1.15 billion expected, non-GAAP operating income of $334 million with $268 million, and adjusted EPS of $0.81 with $0.65.
Wall St Engine cites a $1.2 billion estimate for fourth-quarter revenue and $4.48 billion for the full year, against guidance of $4.515 billion to $4.525 billion.
The Reaction on X
Wall St Engine posted its results card at 12:03Z. Its comments section quotes the same two Pomel lines as the release, and its announcements line reads “Scout: 1.0 launched; powers Bits Investigation”.
The Transcript posted at 14:41Z a line it attributes to Pomel on the call: “…we executed a strong Q3. We saw strength across our business, including across our product lines and across our diverse customer base”. We have not read the call transcript ourselves.
How the Stock Reacted
Datadog shares were down 14.1% at $189.46 at 12:09 p.m. ET (17:09Z) on 4 November, against the 3 November close, according to Nasdaq.com. That is an intraday price, not a close. The Transcript’s post had put the day’s fall at 13%.
What the Risk Factors Say
When we checked EDGAR at 17:02Z on 4 November, Datadog had not filed its 10-Q for the quarter, so this piece has no risk-factor comparison.
As we read the guidance, the fourth-quarter range is the only part of the outlook that sits at the prior quarter’s level; in each of the last two years the fourth quarter came in above the third, by our arithmetic from the filings.
As we read the release, Datadog’s AI story is about its own specialized model, Scout 1.0, which it says matches frontier-model performance at a fraction of the inference cost; it gives no revenue figure for AI-native customers.
“We are seeing strong adoption across our platform as customers scale their digital operations and use of AI”
Three Implications
FOR THE GROWTH RATE The fourth-quarter range implies about 25% growth, against 32.2%, 35.6% and 35.2% in the first three quarters of 2026, by our arithmetic.
FOR MARGINS Guided non-GAAP operating income is a 23.5% to 24.2% margin, against 27.9% in the third quarter, by our arithmetic.
FOR CASH Datadog generated $290 million of operating cash flow and $251 million of free cash flow in the quarter and held $5.2 billion of cash and marketable securities.
The framework puts it this way: “What emerges is a barbelled market structure where software companies must choose between racing to the commoditization floor or climbing to the embedding ceiling.”
As we read it, Datadog’s release points to the embedding side: about 4,860 customers with $100,000 or more of ARR, up 20%, and its own model built for production incidents. The framework, published in December 2025, does not discuss Datadog.
The release does not explain the fourth-quarter range, does not give revenue from AI-native customers and does not give Scout’s cost figures. Guidance is the company’s outlook. We did not read the earnings call ourselves; the one call line is as The Transcript posted it. We did not contact Datadog.
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Datadog grew revenue 35% to $1.20 billion and generated $251 million of free cash flow. Its fourth-quarter range of $1.19 billion to $1.20 billion implies growth of 24.8% to 25.9%, at about the third quarter’s level, by our arithmetic.
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A note on sourcing. Datadog’s financial figures come from its third-quarter 2026 release, filed as Exhibit 99.1 to a Form 8-K on SEC EDGAR on 4 November 2026, and from its Forms 10-Q and 10-K via SEC XBRL. Estimates are the consensus figures cited by Wall St Engine. The one call line is as posted by The Transcript on X; the share move is a Nasdaq.com intraday last sale read at 17:09 UTC. Growth rates, margins and the fourth-quarter 2025 figure are our arithmetic.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
