Datadog’s second quarter was defined by strong customer adoption of its cloud monitoring platform, particularly among AI-native businesses. Management credited higher usage growth from both existing and new customers, with AI-native companies contributing a rising share of revenue. CEO Olivier Pomel pointed to “rapid usage growth with their [AI-native customers’] products,” as well as steady demand across other customer groups. The quarter also saw increased product adoption, with a notable uptick in multi-product usage and strong traction for security offerings. Despite surpassing analyst expectations, management acknowledged the potential for volatility in usage patterns among large AI customers.
Is now the time to buy DDOG? Find out in our full research report (it’s free).
Datadog (DDOG) Q2 CY2025 Highlights:
- Revenue: $826.8 million vs analyst estimates of $791.2 million (28.1% year-on-year growth, 4.5% beat)
- Adjusted EPS: $0.46 vs analyst estimates of $0.41 (12.8% beat)
- Adjusted Operating Income: $164.1 million vs analyst estimates of $150.2 million (19.8% margin, 9.3% beat)
- The company lifted its revenue guidance for the full year to $3.32 billion at the midpoint from $3.23 billion, a 2.9% increase
- Management raised its full-year Adjusted EPS guidance to $1.82 at the midpoint, a 7.4% increase
- Operating Margin: -4.3%, down from 2% in the same quarter last year
- Customers: 3,850 customers paying more than $100,000 annually
- Annual Recurring Revenue: $3.47 billion vs analyst estimates of $3.28 billion (28.1% year-on-year growth, 5.9% beat)
- Billings: $852.4 million at quarter end, up 27.7% year on year
- Market Capitalization: $44.89 billion
While we enjoy listening to the management's commentary, our favorite part of earnings calls are the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention.
Our Top 5 Analyst Questions From Datadog’s Q2 Earnings Call
- Raimo Lenschow (Barclays): Asked how AI observability demand will expand to traditional enterprises; CEO Olivier Pomel explained that as all industries adopt AI, the need for observability will grow, not just among AI-native customers.
- Sanjit Kumar Singh (Morgan Stanley): Questioned how Datadog balances strong guidance with potential AI cohort volatility; CFO David Obstler stated guidance incorporates conservative assumptions due to possible contract and usage variability.
- Matthew Vincent Martino (Goldman Sachs): Inquired about trends in enterprise versus SMB usage; Obstler noted stable enterprise usage and gradual improvement among SMBs.
- Koji Ikeda (Bank of America): Asked about contract visibility with large AI-native clients; Pomel said engagement is strong but acknowledged possible short-term revenue volatility as these customers renegotiate or optimize usage.
- Karl Emil Keirstead (UBS): Probed if AI-native revenue carries different margins; Obstler clarified that margins are driven by customer size and contract terms, not AI status.
Catalysts in Upcoming Quarters
In coming quarters, the StockStory team will monitor (1) the pace at which traditional enterprises adopt AI observability solutions, (2) the success of new AI agent and security product deployments in driving multi-product deals, and (3) progress on margin improvement from cloud efficiency projects. We will also track Datadog’s ability to expand internationally and the impact of any contract renegotiations with large AI-native customers.
Datadog currently trades at $128.71, down from $137.04 just before the earnings. Is the company at an inflection point that warrants a buy or sell? Find out in our full research report (it’s free).
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