Is the rise unfinished after the stock price doubled? Datadog (DDOG.US) was further bullish on Wall Street before the results

The Zhitong Finance App learned that the stock price of Datadog (DDOG.US) has risen by about 106% during the year, but Wall Street still gave room to rise before the third quarterly report: UBS and Oppenheimer raised their target prices on the same day, pointing to the demand for AI observability and the possible increase in expenses of OpenAI. However, both institutions have acknowledged that valuation is still a key risk for this stock.

At the stock price level, Datadog fell slightly by 0.8% before the market on Tuesday, after closing up nearly 4% on Monday — closing at $280.24, up 3.93%, with a total market capitalization of about US$100.6 billion, with a cumulative increase of 106.07% during the year. The three-quarter report is scheduled to be released on November 4, and analysts agree to expect revenue of $1.14 billion and earnings per share of $0.64.

Wall Street is bullish

UBS: Target price rises to $280 to $320, but bluntly says it's “expensive”

UBS analyst Karl Keirstead raised Datadog's target price from $280 to $320, maintaining a “buy” rating, implying an upward margin of about 14% from the previous closing price. He is optimistic that AI-related monitoring services will contribute more to the company's growth in 2027, and suggests that OpenAI may experience higher expenses in the second half of the year, which will provide an additional boost to Datadog's business.

The other half of the same report is a reminder. UBS notes that Datadog's growth is “expensive” compared to its expectations: the company is currently trading around 17 times expected revenue in 2027 and 57 times free cash flow. This means that once growth falls short of expectations, stock prices will be under pressure.

This level of exposure to OpenAI is both a story and a weakness. At the second-quarter earnings conference call, the third quarter guidelines given by the company clearly included the assumption of “decline in usage by the largest customers”; retreating OpenAI as an incremental source is tantamount to rewriting the same variable from a minus to a plus, and its credibility can only be tested on November 4.

Oppenheimer: Target Price Rises to $300 to $330, Seeing Revenue Exceed Consensus Expectations

Oppenheimer raised the target price from $300 to $330, reaffirming the “outperforming market” rating. The agency expects Datadog's third-quarter revenue to be more than 4% higher than the current Wall Street consensus, and expressed confidence in the company's business and management's strategic execution.

In terms of consensus revenue of $1.14 billion, “more than 4% higher” means Oppenheimer's expectations are around $1.19 billion — which is already significantly higher than the company's own third-quarter guidance range of $1,135 million to $1,145 million. In other words, the agency is betting that the company's guidelines are conservative.

Bernstein's reversal: Token consumption increased by at least 50% month-on-month

Bernstein analyst Peter Weed raised Datadog from “equal to the market” to “outperforming the market” on October 19, and raised the target price from $237 to $350. He acknowledged that previous judgments about corporate budgets, implementation thresholds, and consumer side saturation would weigh down 2027 spending — “Our imagination has clearly failed us.”

What supports the reversal is alternative data: enterprise-side token consumption of the largest AI labs increased by at least 50% month-on-month, and smaller AI-native enterprises may be faster; the launch of consumer-side AI agents (such as Muse and Dots) has increased user engagement, and should also boost traditional customer demand for observability products. Based on this, Bernstein raised the 2026 earnings per share forecast to $2.82 and anticipates a further increase to $4.00 in 2027, and these revisions do not assume any improvement in traditional customer fundamentals.

The same report also kept the opposite: Bernstein suggested that Datadog's traditional customer base (accounting for about 85% of revenue) showed signs of weakening at the end of the year. Native AI customers are accelerating at a small base, while much larger traditional observability businesses may be cooling down — that's the tension within this report.

Pre-financial baseline: high growth, weak margins, single customer variables

To determine whether the above expectations are reasonable, a baseline needs to be set out. Datadog's revenue for the second quarter (ending June 30) was US$1.12 billion, up 36% year over year, above the upper limit of the previous guidance range; non-GAAP operating profit of US$257 million, profit margin of 23%, free cash flow of US$279 million, profit margin 25%, and year-end cash and marketable securities of approximately US$5 billion. GAAP operating profit was only $5 million, GAAP operating margin was 0%, GAAP diluted earnings per share of $0.12, and non-GAAP diluted earnings of $0.65 per share (above the consensus of $0.58).

The customer structure is concentrated in the past: about 4,720 customers with ARR above $100,000, an increase of 23% over about 3,850 in the same period last year, contributing about 91% of ARR; the total number of customers is about 33,400. In terms of product cross-selling, 58% of customers used 4 or more products (52% last year), and 37% used 6 or more products (29% last year).

The company's guidance for the third quarter was revenue of $1,135 million to $1,145 million (up about 28% — 29% year over year), non-GAAP operating profit of $260 million to $270 million, non-GAAP earnings of $0.63-0.65; full-year guidance revenue of $4.45 billion to $4.47 billion, and non-GAAP earnings per share of $2.50-2.54. Management says the guidelines are conservative and account for the decline in usage by the largest customers.

This is where the difference lies: the 36% growth rate in the second quarter was only 28% to 29% in the third quarter, down about 7 percentage points in one quarter, and the reason was attributed to a single customer. Bernstein put this more bluntly in his October 19 report — the previous downgrade was based on a reduction in ARR of around $100 million for the biggest “AI native” customer (the report indicates OpenAI).

Product side: AI is not only a requirement, but also a way to sell

To determine whether AI is a “story” or an “order,” it still depends on what the company itself has delivered. In Q2, Datadog launched more than 100 new capabilities at DASH 2026, including: autonomous Bits AI for end-to-end event detection, investigation, and repair; AI Guard to protect AI agents from tip injection and poisoning attacks; Bring Your Own Cloud, which supports deployment within the customer's own environment; and Bits Agent Builder to create custom AI agents. At the same time, the company acquired cutting-edge AI startup Adaptive ML and moved into the direction of enhanced learning operation and maintenance. In his upgrade report, Bernstein also named cybersecurity requirements and Scout v1.0, the company's AI agent for site reliability engineering.

What these products have in common is that they don't sell computing power, but “who will watch after the AI runs”. This also explains why UBS is putting the increments until 2027 — monitoring requirements are naturally lagging behind deployment.

What to watch on November 4?

Three things determine whether this “optimistic after doubling” can be established: first, whether revenue can exceed the consensus by more than 4%, which is significantly higher than the company's own guideline limit; second, whether usage by the largest customers continues to decline or is being reimbursed, which directly corresponds to the OpenAI spending variables mentioned by UBS; third, can management's qualitative assessment of 2027 support the “increasing contribution of AI monitoring” narrative. If the three only fulfill price expectations and there is no evidence from fundamentals, 17 times the estimated 2027 revenue is exactly what UBS says “growth falls short of expectations and there will be pressure”.

The other side: differences in valuation, retail sentiment, and buyout rumors

Valuation is the most direct constraint. Datadog's current price-earnings ratio (TTM) is about 560 times, and the net price-earnings ratio is about 23 times; the 44 institutions integrated with the market platform target average price are about 296.91 US dollars, the highest target price is 350 US dollars, and the minimum price is 158 US dollars — the difference is extremely wide. Retail sentiment is moving in the opposite direction. Retail sentiment surrounding the stock on Stocktwits dropped from “neutral” to “bearish.”

The purchase line is also yet to be settled. Last week it was reported that Datadog plans to expand its cybersecurity business through the acquisition of cloud security startup Upwind (Upwind's software monitors cloud applications, including AI agents). However, there are conflicting reports about the deal: the media said on October 22 that Datadog's bid for nearly $4 billion was rejected by Upwind, and Upwind is completing $300 million financing at a valuation of about $3.8 billion. Both companies have not publicly commented, and the deal is currently only an unconfirmed market rumor.