Datadog (DDOG) or Dynatrace (DT): which stock to pick?
2026-07-20 · By Lubin Danilo, founder of Lubin Investment
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Datadog and Dynatrace both monitor the technical health of companies' IT systems, and both score solidly in my quality filter. But Datadog trades at more than four times Dynatrace's multiple relative to the cash it generates, and is priced today at the highest point of its own history. Here's what my quality and valuation filter reveals about both.
Two companies doing the same job: monitoring IT systems
When an app crashes, an e-commerce site slows down on a high-traffic day, or a cloud server goes down at 3 a.m., someone needs to know before customers do. That's the business of Datadog and Dynatrace: dashboards and alerts that continuously monitor the health of thousands of servers, databases, applications, and increasingly, AI agents. This market is called observability (the word comes from control theory: the ability to infer a system's internal state from what can be observed externally).
Datadog was named a Leader in the Gartner Magic Quadrant for Observability for the sixth consecutive year in July 2026, and just extended its platform to monitor AI agents and applications built on large language models. Dynatrace, for its part, was recognized as a Leader in the same ranking for the sixteenth time, and launched Dynatrace Intelligence in 2026, a layer combining deterministic analytics with generative AI to automatically diagnose an outage, built on Grail, its unified data lakehouse. Both are therefore reference players recognized by the same analysts, in the same market.
The comparison table
| Criterion | Datadog (DDOG) | Dynatrace (DT) |
|---|---|---|
| Quality score | 8 out of 10 criteria | 8 out of 10 criteria |
| Valuation (P/FCF) | 345.6x annual cash | 80.8x annual cash |
| Position in its own 5-year history | Most expensive point ever observed (100th percentile) | Lower half of its own history (35th percentile) |
| Revenue growth (5 years) | 29.5%/year | 22.7%/year |
| Return on capital employed (Cash ROCE) | 6.3% (fails my criterion) | 48.6% (comfortably passes my criterion) |
| Net margin | 3.7% | 8.1% |
| Net debt | 2.0 years of cash | Net cash position |
| Market cap | about $83.3 billion | about $12.3 billion |
Why these criteria, and what they reveal
The score out of 10 judges business quality independent of price: profitability, sales and cash growth, discipline on share count, debt, return on invested capital, consistency over several years. Both companies get the same overall score, but not for the same reasons, and that's where the analysis gets interesting. Cash ROCE (return on capital employed, calculated on cash generated rather than accounting profit) measures how much cash a company produces for every dollar of capital it employs. Dynatrace generates 48.6 cents for every dollar of capital invested, an excellent figure that comfortably passes my criterion. Datadog generates only 6.3 cents, below my threshold: the company invests heavily (R&D, cloud infrastructure, acquisitions) for every dollar of cash it currently gets back.
That's not necessarily a flaw: Datadog may be investing for faster future growth (it already shows 29.5% annual revenue growth versus 22.7% for Dynatrace). But it means its current return on capital employed is lower, and the market is betting on a future conversion of that growth into cash, not on a return already proven today.
Datadog: the fastest growth, at the highest price in its own history
Datadog counts about 4,550 customers paying it more than $100,000 a year each, up 21% year over year, and its revenue has grown more than fivefold since 2020 (from $603 million to $3.43 billion). Its cash dynamics are real: its free cash flow margin is improving, and its cash conversion cycle (the delay between paying suppliers and collecting from customers) is negative, at -19 days. In practice, Datadog collects money from its customers before even paying its own bills, a very favorable cash dynamic typical of software sold on annual subscriptions paid upfront.
But one point deserves close attention: stock-based compensation reached $750 million in 2025, about 75% of the free cash flow generated that same year. A large share of the cash the company generates therefore goes toward offsetting shareholder dilution rather than funding growth or returning cash directly to shareholders. And crucially: at the current price of $263.20, Datadog trades at 345.6 times its annual cash, the most expensive point in its five-year history (100th percentile, literally the highest ever observed). My reasonable buy price for Datadog comes out at $37.69, an 85.7% premium versus the current price.
Dynatrace: slower growth, but a real dilution trap
Dynatrace crossed $2 billion in annual recurring revenue and delivered a fourth consecutive quarter of 16% constant-currency growth in that metric. On paper, Dynatrace trades at 80.8 times its cash, four times cheaper than Datadog, and sits in the lower half of its own valuation history (35th percentile), rather than at a peak.
But my free-cash-flow-per-share growth criterion fails for Dynatrace, at -0.7% a year over five years, even though its gross cash generated more than doubled over the period (from $206 million to $433 million). The explanation: share count rose every year to fund stock-based compensation, which nearly quadrupled over the period (from $58 million to $272 million). Once that dilution is stripped out, the cash actually available per shareholder is flat. Its cash conversion cycle is also longer than Datadog's, at 77 days, consistent with heavier enterprise contracts and longer billing cycles. My reasonable buy price for Dynatrace comes out at $12.76, versus a current price of $44.71, a 71.5% premium.
So, which one should you pick?
I walk through the full growth-adjusted pricing logic in my guide to the PEG ratio. Neither is buyable today under my strict model: both trade well above my reasonable buy price. But the nature of the premium differs. With Datadog, you're paying for the sector's fastest growth at the single highest price ever observed for this specific stock: the risk is that a simple normalization toward its own historical average (not a collapse) would be enough to hurt if growth ever slows. With Dynatrace, you're paying for a company that's more profitable on its capital (Cash ROCE almost eight times higher), at a price closer to its own historical norm, but whose real per-share value creation is held back by dilution: the growth is there, but it hasn't yet fully translated into cash per shareholder.
If I had to sum up the choice: Datadog suits someone who believes the AI observability market will keep accelerating and is willing to pay top price for that conviction; Dynatrace suits someone who prefers a company already profitable on its capital, provided the dilution finally slows down. Either way, my advice stays the same: wait for a price closer to my buy threshold rather than paying today's premium.
- Datadog and Dynatrace get the same quality score in my filter, but for opposite reasons: Datadog grows faster but converts capital into cash less efficiently (Cash ROCE 6.3%); Dynatrace converts capital very efficiently (Cash ROCE 48.6%) but its growth slows once dilution is stripped out.
- Datadog trades at 345.6 times its annual cash, the most expensive point in its five-year history (100th percentile); Dynatrace trades at 80.8 times its cash, in the lower half of its own history (35th percentile).
- Stock-based compensation represents a very high share of free cash flow for both (75% at Datadog), and explains the slowdown in cash per share at Dynatrace despite rising gross cash.
- Neither is below my reasonable buy price today: both show a premium above 70% under my strict model.
FAQ
Datadog or Dynatrace, which one is cheaper?
In absolute terms, Dynatrace trades at 80.8 times its annual cash versus 345.6 times for Datadog, so Dynatrace is nominally cheaper. But neither is below my reasonable buy price: both show a premium above 70%.
Why does Datadog have such a low Cash ROCE despite strong growth?
Cash ROCE measures cash generated per dollar of capital employed. Datadog invests heavily (R&D, cloud infrastructure, acquisitions) to sustain its current 29.5% annual growth, which mechanically lowers its return on already-committed capital, even if that growth may convert into cash later.
What is IT observability?
Observability is the ability to understand the internal state of an IT system (servers, applications, databases) from what can be observed externally: logs, metrics, request traces. Platforms like Datadog and Dynatrace centralize these signals to alert technical teams before, or as soon as, a problem occurs.
Why does Dynatrace fail the cash-per-share growth criterion?
Because shares outstanding rise every year to fund stock-based compensation, which nearly quadrupled in five years. Once that dilution is stripped out, the cash actually available per shareholder is flat, despite the company's gross cash more than doubling over the same period.
Should you buy either stock now?
Under my strict model, no: both trade well above my reasonable buy price (85.7% premium for Datadog, 71.5% for Dynatrace). This is not personalized investment advice, do your own research.
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About the author
Written by Lubin Danilo, founder of Lubin Investment. A self-taught individual investor, I find fundamental analysis fascinating, and it has delivered excellent results. For three years now, my performance has beaten the S&P 500. But analyzing every stock took too much time: sites with incomplete data, calculation methods and criteria never aligned with mine. And spotting the best stocks was just as time-consuming, even with my own well-defined checklist. So I put my software development background to work to build this software, base my investment strategy on its results, and share it with people who share the same passion as me. It judges a company's quality and its price separately, using criteria drawn from the financial literature (Warren Buffett, Michael Mauboussin, Aswath Damodaran).