I have recently begun taking a closer look at an old board favorite, DataDog (DDOG). I sometimes take a peek at old portfolio positions both as a learning exercise, and to see if anything interesting might have changed about the company. In doing so, I noted the two most recent quarters were far better than typical.
Below is a summary of diving a bit deeper into what has changed. I currently have no position in DDOG, but am considering opening a small position as the current stock price may represent an opportunity.
Overview
Datadog, operates an observability and security platform for cloud applications.
When I first invested in October 2019, DataDog provided web application monitoring and (often related) security monitoring. My take on their advantage over competition at the time was the ease of integrating their product into existing applications combined with a reporting system that provided an unrivaled level of insight into application performance and security. Since 2019, DataDog has shifted slightly to software observability, with a recent focus on AI applications.
Revenue and Earnings History
| EPS (non-GAAP) | Fiscal Quarter | ||||
|---|---|---|---|---|---|
| Fiscal Year | 1 | 2 | 3 | 4 | Total |
| 2022 | $ 0.03 | $ (0.02) | $ (0.08) | $ (0.09) | $ (0.16) |
| 2023 | $ (0.08) | $ (0.01) | $ 0.06 | $ 0.44 | $ 0.41 |
| 2024 | $ 0.44 | $ 0.43 | $ 0.46 | $ 0.49 | $ 1.82 |
| 2025 | $ 0.46 | $ 0.46 | $ 0.55 | $ 0.56 * | $ 2.03 |
| Revenue | Fiscal Quarter | ||||
|---|---|---|---|---|---|
| Fiscal Year | 1 | 2 | 3 | 4 | Total |
| 2022 | $ 363,030 | $ 406,138 | $ 436,533 | $ 469,399 | $ 1,675,100 |
| 2023 | $ 481,714 | $ 509,460 | $ 567,536 | $ 589,649 | $ 2,148,359 |
| 2024 | $ 611,253 | $ 645,279 | $ 690,016 | $ 737,727 | $ 2,684,275 |
| 2025 | $ 761,535 | $ 826,760 | $ 885,651 | $ 916,000 * | $ 3,389,946 |
| Revenue YoY Growth | Fiscal Quarter | |||
|---|---|---|---|---|
| Fiscal Year | 1 | 2 | 3 | 4 |
| 2022 | 82.84% | 73.90% | 61.39% | 43.90% |
| 2023 | 32.69% | 25.44% | 30.01% | 25.62% |
| 2024 | 26.89% | 26.66% | 21.58% | 25.11% |
| 2025 | 24.59% | 28.12% | 28.35% | 24.17% * |
| Revenue Seq Growth | Fiscal Quarter | |||
|---|---|---|---|---|
| Fiscal Year | 1 | 2 | 3 | 4 |
| 2022 | 11.29% | 11.87% | 7.48% | 7.53% |
| 2023 | 2.62% | 5.76% | 11.40% | 3.90% |
| 2024 | 3.66% | 5.57% | 6.93% | 6.91% |
| 2025 | 3.23% | 8.56% | 7.12% | 3.43% * |
* FY2025Q4 numbers are forecast projections from the FY2026Q3 Earnings Press Release using the high end of projected earnings/revenue.
Other numbers of interest:
- Profitable on both GAAP and non-GAAP metrics
- non-GAAP Gross Margin 81%
- non-GAAP Operating Margin 23%
- No stock based compensation, no share dilution.
Interesting Quotes
Year-Over-Year revenue growth of 28% for the past two quarters (FY2025Q2 and FY2025Q3) caught my attention. The source of this growth is noted in the FY2025Q2 earnings call:
Source of revenue growth, David M. Obstler, CFO:
We saw a continued rise in contribution from AI native customers in the quarter who represented about 11% of Q2 revenues, up from 8% of revenues in the last quarter and about 4% of revenues in the year ago quarter. The AI native customers contributed about 10 points of year-over-year revenue growth in Q2 versus about 6 points last quarter and about 2 points in the year ago quarter.Now as previously discussed, we do see revenue concentration in this cohort in recent quarters. But if we look at our revenue without the largest customer in the AI native cohort, our year-over-year revenue growth in Q2 was stable relative to Q1.
Of particular note related to this growth is a recent increase in R&D expense:
Bert Hochfeld notes R&D is increasing (2025-08-21).
[…] the company has substantially increased its R&D spend which was an elevated 32% of revenue last quarter and up 45% year on year and up by 16% sequentially. It is very rare to see a company of this scale spend 32% of revenue on research and development.
In the same article, Bert Hochfeld later notes significant new AI offerings for DataDog customers:
The company announced a slew of intelligent agents. In all it announced 125 new features and SKUs at its user conference held in June. It would be tedious and not all that useful to discuss all of the different products that Datadog has now announced. The company has a specific SKU that it announced which monitors the usage and performance of GPUs.
Revenue from AI native customers is dominated by one customer: OpenAI. Bert Hochfeld has musings on the potential risk involved here:
OpenAI is, of course, the leading customer in the AI Native segment. So, some investors and analysts are concerned that this segment of Datadog’s business will face slowing growth if OpenAI either develops more of its own observability functionality or if it moves some workloads to Chronosphere. Building an alternative to Datadog’s functionality internally seems very unlikely. OpenAI is not in the observability business and its expertise lies in models (LLMs), an area quite a bit different from the use of observability to optimize the performance of its network.
I highly recommend Bert Hochfeld’s article for further insights into how DataDog interacts with AI customers.
Notable quotes from the FY2025Q3 Earnings Call Transcript:
Olivier Pomel, CEO:
As a notable inflection, we saw acceleration of year-over-year revenue growth across our non-AI customers. And the sequential usage growth for non-AI existing customers was the highest we have seen going back 2 quarters. This growth was broad-based as our customers are adopting more products and getting more value from the Datadog platform.
We also experienced strong revenue growth for our AI native customers and a broadening contribution to growth among those customers. There, too, we saw an acceleration of growth in our AI cohort in Q3 when excluding our largest customer.
While AI growth has been pushed hard, customer feedback has been very positive. One example from many provided in the earnings call:
Oliver Pomel, CEO
As one user recently told us, “With Bits AI SRE being on call 24/7 for us, meantime resolution for our services has improved significantly. For most cases, the investigation is already taken care of well before our engineers sit down and open their laptops to assess the issue.” And this is not an isolated comment. We see the potential here for our agents who radically transform observability and operations.
Q&A: On Growth Sustainability
Question: I wanted to ask a question on the inflection in the non-AI native growth and how to think about the areas of strength in this cohort. Is it coming from your largest enterprises? Is it coming from a certain type of customer? Is there a common theme in the workloads that you’re seeing or the products that are being added on that is driving that strength? Or is it just really just broad-based? What I’m trying to get out here is I’m really trying to understand more the durability of this growth of collection.Oliver Pomel, CEO:
So it is broad-based. And I think, again, speaks to a couple of things. It speaks to the fact that, in general, the demand environment is good. Though I would say, there’s been a very, very high growth of hyperscaler revenue that over the past – next generation for the hyperscalers in general. A lot of that is GPU related, but the growth we’re seeing here and the exception we’re seeing here is largely not GPU-related livery, but not autonomy. So that’s not exactly what you’ve seen with some of the other vendors there. .One reason this is broad-based is these are the same products we sell to all customers, and this is largely the same go- to-market organization that we have a few segments, but – and we’ve been doing well executing there. I think we’ve invested quite a bit in product, and we keep and we will keep doing it, and we see the results of that.
David M. Obstler, CEO:
I’ll add that it’s across the customer base, enterprise SMB. And when we look at it, it’s not just an AI SMB. If you remove these AI companies, you still see a strengthening SMB demand cycle going on. And unlike in previous periods, it also is across spending ranges. We’re not seeing larger spenders or smaller spenders. We’re just seeing a broad trend of improved demand across the spending trends.
The earnings call has many insights into how DataDog products are being used by customers and potential drivers of demand. While it is worth a read, I have not included comments from the Q&A because I find that sort of information makes it too easy to let hope for what is possible overshadow what the numbers are saying about real trends.
Personal Musings on Risk Assessment
I see two macroeconomic trends that are particularly relevant to evaluating risks for DataDog at the moment:
- A common belief that “AI is eating software”, meaning non-AI software companies will soon be irrelevant.
- A belief that AI, as an investment, is in dot-com style bubble territory.
The first concern seems proven false as it relates to DataDog, as shown by reading through recent earnings releases and Bert Hochfeld’s article from August. Yet the wider market fear is likely effecting investor sentiment and the stock price. I have so far only skimmed through articles on DataDog from other sources, but have not seen yet seen any compelling argument against my perspective. I consider this very low risk.
The second point is of more concern. DataDog had fallen off my radar of possible investments for lack of growth potential. While AI has proved a boon by way of increasing TAM and new providing important new AI-based tools to all customers, an AI bubble bursting could have a severe impact on DataDog. Personally, I do not give any credence to the current AI bubble fears, but a related concern is highly relevant here: Even without a major bubble bursting event, there will undoubtedly be major changes in winners and losers among software companies as AI evolves. This could have drastic effects on DataDog customers, both among traditional software companies and more recent AI native customers. I have no way of evaluating this risk in a concrete way, so consider it a high risk which requires careful monitoring.
Internally to the company, I have some concern at the rate at which DataDog is expanding their new offerings. This has been a very ambitious year for their R&D team and 2026 looks to be equally ambitious. Countering this, DataDog is still a founder led company (Oliver Pomel, the CEO) with significant experience in general needs of their customers. Giving the benefit of the doubt, I asses this as a low risk, but one which still requires monitoring. The continued high margins are also comforting here.
The stock price for DDOG may be down 30% from its recent high, but it is still not what I would call cheap when evaluating P/E and EV/S ratios. Yet these ratios look far more compelling than they have in years, thanks to the combination of two very good quarters and the recent 30% drop in price over the past two months.
Guidance for FY2025Q4 is low compared to recent quarters (24% YoY revenue increase, down from 28% in Q3). DataDog always guides conservatively, but a 4% surprise for a continued 28% rate of growth seems too much to hope for. Medium risk.
I am not certain DataDog has sufficient room to grow from our Saul-based criteria. DDOG already has a market cap of $48B. I admit, I am not great at evaluating growth potential of a company. High risk here until I have a better understanding.
