🚨 Don't buy stocks just by reading the news. The 'inconvenient truth' revealed by primary data from Datadog's earnings

In the world of investing, there are always two worlds. One is the world of the 'narratives' that the media writes about so spectacularly. The other is the world of 'facts' etched into corporate financial statements.

On May 7, 2026, Datadog, a leader in cloud monitoring platforms, announced its first-quarter earnings, which sent the market into a frenzy. The stock price surged by 30% at one point. Media outlets are all reporting on its breakthrough, calling it the 'largest gain in history' and the 'champion of the AI era.'

However, do those news headlines really reflect the true state of the company?

The 'Datadog surge' reported by the media

First, let's organize the information reported by a major online brokerage-affiliated media outlet. It is filled with attractive words that would make any investor want to jump in.

• Breaking the $1 billion mark: Revenue increased by 32% year-on-year.

• Awakening as an AI stock: Newly introduced GPU monitoring products have become essential for LLM inference pipelines.

• Liberation from geopolitical risk: 'Only code is shipped.' An invincible business model not subject to physical constraints.

Reading just this, Datadog looks like an 'infrastructure of the AI era' with no blind spots. However, we know that 'what is truly important is not the headline numbers themselves, but the numbers behind them.'

The attempt of this article: How much can the news be 'trusted'?

In this article, we will dare to start by doubting this 'information presented by the media.' What kind of primary information is hidden behind the positive information cherry-picked by the media?

We will delve into the latest quarterly report (10-Q) and earnings press release to thoroughly compare the news content with the primary information.

• Is the quality of the '32% revenue growth' emphasized by the news consistent with cash flow?

• Can the contribution of AI-related products be objectively confirmed from financial data?

• Does the upwardly revised full-year outlook contain excessive optimism?

By passing through the filter of the media, information is often processed to look 'beautiful.' When we remove that filter and compare it with the raw data, what kind of landscape will we see?

Before diving into primary information: Who is Datadog?

Before looking at the 'results'—the numbers in the financial statements—let's dissect the 'process' of how they achieve those numbers through their business.

To describe Datadog in one word, it is the 'ultimate behind-the-scenes player that monitors and diagnoses the health of increasingly complex IT systems in real-time.'

It is called an 'observability platform' in technical terms, but there is no need to overthink it. Modern companies run services by linking countless programs on clouds like Amazon Web Services (AWS) and Microsoft Azure. However, the more complex the system becomes, the harder it is to pinpoint 'where the error is occurring' or 'why it is running slowly.'

Datadog is a tool that sheds light on this chaotic state.

The 'three types of blood' they collect

Datadog's strength lies in its ability to seamlessly integrate the following three types of data, which are often managed separately, into a single dashboard.

1. Metrics (numerical values): Basic data like the 'blood pressure and heart rate' of a system, such as CPU usage and traffic volume.

2. Traces (tracking data): The 'flow' that shows which programs a user's request passed through to be processed.

3. Logs (text): Detailed records of 'when and what happened' that the system outputs.

For example, when a 'payment error occurs on an e-commerce site,' an engineer can instantly identify which server, which program, and which code is the cause just by looking at the Datadog screen.

Datadog's 'powerful alchemy'

There is a clear reason why their business model is highly valued by investors.

• 'Land and Expand' strategy Initially, a single engineering team adopts an inexpensive, single product (such as just log management) (Land). However, due to its ease of use, it eventually spreads by word-of-mouth to other teams, and they continue to add functions (modules) to use, such as security monitoring and database monitoring (Expand).

• Extremely high switching costs (difficulty of cancellation) Once Datadog is integrated into the entire system and established in daily work flows, switching to a cheaper monitoring tool from another company is a daunting task. This makes their revenue base as solid as bedrock.

• A new tailwind called AI As mentioned in the news at the beginning, the movement of companies incorporating AI (such as large language models) into their own systems is accelerating. Because the operating environment for AI is more complex and prone to becoming a black box than conventional systems, a new, massive demand for 'monitoring AI behavior' is being born.

Now, you are ready for a fact check

'Essential infrastructure for the cloud era,' 'once you use it, you can't let go,' and 'benefiting from AI demand.' Looking only at the business model, it is truly an excellent company with no blind spots. It is understandable why the media is collectively praising it as the 'champion of the AI era.'

However, we must pause here.

Is this seemingly perfect business model truly reflected without any distortion in the 'latest earnings figures (primary information)'? Are they earning cash commensurate with their sales growth?

From here on, let's leave the frenzy of the news behind and dive into the sea of cold, hard facts known as the latest 👉'10-Q (Quarterly Report)' that Datadog submitted to the Securities and Exchange Commission (SEC).

Fact check with primary information: The 'truth' told by the Profit and Loss Statement (PL)

To what extent is the spectacular news reported by the media actually backed by financial figures? I will dissect the Profit and Loss (P&L) statement for the first quarter of 2026 from the latest quarterly report (10-Q) filed with the SEC (U.S. Securities and Exchange Commission).

Verification 1: Is '32% revenue growth, surpassing $1 billion for the first time' true?

The top-line (revenue) growth, which was the biggest headline in the news. This is self-evident when looking at the primary information.

• 2025 Q1 Revenue: 761,553 thousand dollars (approx. $760 million)

• 2026 Q1 Revenue: 1,006,426 thousand dollars (approx. $1 billion)

Calculating this, it results in approximately 32.1% growth year-over-year. There is no exaggeration in the '32% increase' and 'surpassing $1 billion' figures reported by the media. It must be said that maintaining a growth speed of over 30% even after the company has grown to this size is phenomenal.

Verification 2: The destructive power of 'only code is shipped'

Where does the superiority of the business model mentioned in news articles—that 'the company is unaffected by costs' and 'only code is shipped'—appear in the financial statements? It is in the 'Gross Margin'.

Let's look at the Gross profit, which is the revenue minus the Cost of revenue directly incurred in providing the service.

• 2026 Q1 Gross profit: 797,198 thousand dollars

• Gross margin: 797,198 ÷ 1,006,426 = approx. 79.2%

For every 100 yen in sales, about 80 yen remains as profit. The overwhelming margin of a 'pure software company' that does not have physical procurement, manufacturing lines, or inventory risk is clearly reflected in this figure. The media's claim that it does not depend on the situation in the Strait of Hormuz is completely backed up by this 79.2% figure.

The 'biggest surprise' the media doesn't talk about: GAAP-based operating profitability

The news stated that the 'Non-GAAP EPS' was good. Companies often like to emphasize Non-GAAP figures that exclude inconvenient numbers such as stock-based compensation expenses.

However, what I want to evaluate most after looking at the primary information is the 'GAAP (Generally Accepted Accounting Principles)-based operating profitability,' which the media has not touched upon much.

• 2025 Q1 Operating income/loss: -12,420 thousand dollars (loss)

• 2026 Q1 Operating income/loss: +7,327 thousand dollars (profitable!)

This quarter, out of $1 billion in revenue, Datadog has poured $435.29 million (a revenue ratio of about 43%!) into Research and development. This is a fierce investment to create new features such as the 'GPU monitoring product for AI development teams' mentioned in the news. Furthermore, they have invested $279.82 million in Sales and marketing.

Even while making such huge upfront investments, they finally achieved profitability in 'GAAP-based operating income,' which indicates the profit from their core business. This is a very important signal that the company has completely transitioned from a 'loss-making SaaS just for growth' to a 'phase where it can grow while generating profit'.

The 'blind spot' of news revealed by primary information: The breakdown of growth as told by the MD&A

The media often reports only the 'final numbers.' However, what you really need to know as an investor is the process of 'how those numbers were created.' When you read the 'Management's Discussion and Analysis of Financial Condition and Results of Operations (MD&A)' section of Datadog's latest 10-Q, three important facts that news articles don't mention emerge.

1. The true driver of 32% revenue growth is 'existing customers'

The news reported that 'revenue reached $1 billion, a 32% increase year-over-year' and 'customers with ARR of $100,000 or more increased to 4,550.' This gives the impression that new customers are flocking in one after another due to AI demand.

However, the description in the primary source is more level-headed and striking.

This single sentence proves the terrifying nature of Datadog's business model. What is driving their phenomenal growth is actually not 'new acquisitions,' but the 'expansion' of existing customers who are increasingly using more features and data volumes. From this data, we can read that the 'AI monitoring' touted by the news will also grow into a reliable revenue source by first being cross-sold to this thick base of existing customers.

2. The trap of 'only code is shipped': The overlooked massive cost of revenue

The most catchy part of the news articles was the claim that 'the physical manufacturing process is irrelevant to the company's costs' and 'only code is shipped.' It is true that they do not own factories, and they have maintained an astonishing gross margin of 79%, unchanged from the previous period.

However, the primary information coldly points out that they are by no means in a 'weightless space unaffected by costs.'

Instead of owning physical factories, Datadog rents out massive 'cloud infrastructure (such as AWS and GCP)' as its own factory. If customers increase their AI workloads and the amount of data to be monitored explodes, the cloud costs paid by Datadog will naturally jump as well.

Since payments to cloud providers increase in proportion to revenue growth, the fact is that the gross margin has 'remained flat' at 79% as a result. It must be said that the media's description of being 'unaffected by costs' is a bit too romantic.

3. The 'gritty investment' that creates GPU monitoring products

The GPU monitoring product that the news praised as 'indispensable for full-scale AI adoption.' The source of how this was created is also engraved in the primary information.

The massive R&D expense of $435 million, equivalent to 43% of revenue. The reality behind this is 'personnel costs' ($70.3 million increase) to hire a large number of talented engineers and product teams, and 'cloud infrastructure investments' ($13.4 million increase) for them to run in development and test environments.

Behind the 'brilliant growth as an AI stock' depicted by the media, there is a gritty yet massive investment in development teams struggling with piles of documentation and vast amounts of code.

Summary: News is the 'result,' primary data is the 'reality'

What has become clear through the comparisons so far is that while the news is by no means lying, it is 'conveniently and overly beautifying' the reality of the company.

The abnormal degree of dependence on existing customers and the existence of heavy 'virtual manufacturing costs' in the form of cloud infrastructure expenses are things that can never be seen without unraveling the raw financial data.

The 'blind spot' of the news revealed by primary data (2): The overwhelming strength told by the balance sheet

The news reported Datadog's 'growth potential' in a spectacular way. However, when you unravel the primary data, the balance sheet, there is a 'defensive power' and 'alchemy' hidden there that is even more surprising than the growth potential.

1. The '4.7 billion dollar fortress' that neutralizes debt

When looking at a company's safety, the balance between cash on hand and debt is one of the most important indicators. Let's look at Datadog's assets as of the end of March 2026.

• Cash and cash equivalents: $426.36 million

• Marketable securities: $4.33225 billion

The total liquidity on hand combining these two reaches an astonishing approximately $4.758 billion. On the other hand, the main long-term debt in the liabilities section, 'Convertible senior notes, net, non-current,' is $984.49 million.

Unlike when auditing the massive debt structures of companies like AMC or McDonald's, there is not a shred of the pressure where debt strangles the company here. It is in a state where it can immediately move cash about five times the amount of interest-bearing debt it holds, a balance sheet like a 'fortress' that can pay off its debts at any time if necessary.

2. The 'SaaS magic' the media doesn't report: $1.2 billion in deferred revenue

There is another strength unique to SaaS companies that can be read from the balance sheet. That is 'Deferred revenue, current' in the liabilities section.

As of the end of March 2026, this amount reaches $1.23115 billion. This refers to the 'amount for which cash has already been received from customers but the service has not yet been fully provided (not recorded as accounting revenue).' In other words, Datadog is in a state where it has already secured over $1.2 billion in 'future revenue' in its hands.

The news reported that 'customers with ARR (Annual Recurring Revenue) of $100,000 or more have increased,' but this primary data of '$1.2 billion in deferred revenue' is the best proof that customers are firmly locked into Datadog's service and want to continue using it even if they have to pay in advance.

3. Accumulation of 'true wealth': Steady buildup of retained earnings

Finally, I want to focus on 'Retained earnings' in the net assets section.

• End of December 2025: $137.78 million

• End of March 2026: $190.36 million

In just one quarter, the accumulation of true profits earned by the company has increased by approximately $52 million. While many companies continue to bleed red ink through upfront investments while only growing their top line, these figures fully confirm that Datadog is growing while strengthening its shareholders' equity.

The 'big twist' revealed by primary information: The mechanism of profitability that the media doesn't report

So far, we have confirmed the robustness of Datadog's income statement (PL) and balance sheet (BS). The headline praised by the media, 'GAAP-based operating profitability (+$7.3 million),' is also an undeniable fact in terms of numbers.

However, when we look deeper into the primary information, flipping through the notes to the financial statements and the 'Statement of Changes in Shareholders' Equity,' we witness a stunning 'big twist' that makes our spines chill.

The true nature of this, which the news doesn't touch upon and analysts who don't read primary information likely won't spot, is 'Stock-based compensation (SBC)'.

The truth about the 'over $200 million' that was hidden

Let's look at the latest submitted data. The total amount of stock-based compensation recorded by Datadog in the first quarter of 2026 reached a staggering $206.03 million. This is a significant increase from the $169.92 million in the same period last year.

In our earlier PL analysis, we evaluated that the company 'achieved GAAP profitability while investing huge R&D expenses ($435.29 million).' However, when we dissect the breakdown, we find that the R&D expenses include $123.67 million in stock-based compensation. Furthermore, $42.29 million in SBC is also hidden within Sales and Marketing expenses.

If paid in 'cash,' it would be an immediate massive deficit

The implications of this are extremely significant.

What would happen if Datadog paid its talented AI engineers and powerful sales force entirely in 'cash' instead of 'company stock'? The $7.3 million in operating profit, which appeared to have successfully turned into a profit on the books, would instantly plummet into an 'operating loss' of approximately $200 million.

The media praised the company's business model unconditionally, saying, 'It has no physical manufacturing process, and only code is shipped.' However, the fact that the primary information coldly presents is different. It wasn't just code that they were shipping in large quantities. By issuing (shipping) large amounts of 'company stock,' they were preventing a massive cash outflow for personnel expenses.

An abnormally high ratio: A company that distributes 'about 4 times' its net income in company stock

The horror of stock-based compensation is not just in the 'size of the amount.' When compared to the 'final profit' the company earned, its abnormality stands out.

Let's line up the 'Net income' at the bottom of the income statement and the 'Stock-based compensation' figures in the Statement of Changes in Shareholders' Equity once more.

• 2026 Q1 Net Income: $52.57 million

• 2026 Q1 Stock-based compensation (SBC): $206.03 million

Have you noticed? Surprisingly, the amount of stock-based compensation issued reached 'approximately 3.9 times (about 392%)' of the net income the company earned in the quarter.

Net income is essentially the 'true wealth for shareholders' that remains after all costs have been paid and taxes settled. However, in Datadog's case, while they promote that 'we have left $52 million in profit for shareholders!', behind the scenes, they are printing 'new shares' worth nearly four times that profit and distributing them to insiders (employees and executives).

'For every $1 of profit earned, they are distributing $4 in company stock.'

This is the other face of the AI champion that the media is raving about. Looking at this ratio, which is like a grim joke where 'compensation exceeds profit,' you can see just how hollow the news headline of 'record-high profits!' really is.

The next question: So, what is happening with 'cash flow'?

Since they are handing out stock without paying cash, no cash is actually leaving their hands.

Media news articles wrote spectacularly that 'free cash flow reached $289 million.' However, now that you know the stark fact of this 'over $200 million in stock-based compensation,' can you really take that cash flow figure at face value?

How does this 'alchemy of company stock' cast a spell on the company's actual cash-generating ability (cash flow)? In the next section, we will finally dissect the final piece of primary information, the 'Cash Flow Statement (CF),' to get closer to the true strength of this company.

The conclusion of the 'big twist' revealed by primary information: Questioning the 'quality' of cash flow

News articles reported the following to promote Datadog's financial health: 'Free cash flow reached $289 million.'

Certainly, the ability to keep cash on hand is a source of corporate value. However, the moment we open the door to the primary information, the 'Cash Flow Statement (CF),' it becomes clear how this '$289 million' figure was 'created.'

More than half of operating cash flow is 'stock-based magic'

Let's look at 'Net cash provided by operating activities,' which shows a company's ability to earn cash. In the first quarter of 2026, Datadog generated $334.62 million in cash.

However, when looking at the breakdown (Adjustments to reconcile net income to net cash provided by operating activities), a surprising item sits there.

• Stock-based compensation, net of amounts capitalized: $196.84 million

This is that massive stock-based compensation we dissected in the previous section. Under accounting rules, compensation paid in company stock is a 'non-cash expense' because no cash actually leaves the company, so it is added back to the net income of $52.57 million.

Do the math. Out of $334.62 million in operating cash flow, in fact, about 58% ($196.84 million) is inflated by this 'add-back of stock-based compensation'.

What if they paid compensation in 'cash'?

What would happen if Datadog paid its talented AI engineers their salaries in 'cash' instead of company stock?

Operating cash flow drops sharply to the $137 million level. Even the 'free cash flow of $289 million' figure praised by the news falls below $100 million once you subtract capital expenditures (Purchases of property and equipment: -$11.35 million) and capitalized software development costs (-$34.17 million).

The 'news figures' and 'primary source figures' carry different weight

To be clear, Datadog is not cooking the books, nor are they breaking any rules. As a US SaaS company, they are adopting an extremely standard and legal strategy.

However, here is the truth that you, as an investor, need to know.

If you only look at the headline 'free cash flow of $289 million' reported by the media, you might mistakenly believe that they earned all of that solely through their powerful ability to collect cash from customers. But if you check the primary source (Raw Data) with your own eyes,the raw reality emerges that more than half of that cash flow is merely 'the result of preventing cash outflow by diluting shareholder equity (issuing company stock)'.

Numbers do not lie, but the filter of news sometimes makes the 'quality' of those numbers invisible.

Final Summary: The identity of the '3-minute sense of unease' taught by hundreds of financial statements

'The background behind Datadog's stock price surge'—starting from a spectacular news article reported by a certain media outlet, we have dived into the depths of the primary source: the latest quarterly report (10-Q).

The 'result figures' reported by the news are certainly not lies.

• Revenue increased by 32% year-on-year, surpassing $1 billion for the first time.

• The gross margin is extremely high at 79%, and it is not constrained by physical costs.

• They have achieved GAAP-based operating profitability, and free cash flow is also abundant.

Looking only at this, Datadog is an 'AI-era infrastructure company' with no blind spots. However, as I went through this stack of primary source documents,I felt a strong 'sense of unease' in just three minutes.

That is by no means intuition or a guess. It comes from 'overwhelming pattern recognition' born from the experience of painstakingly reading through the raw data (financial statements) of hundreds of companies.

'Dressed up' financial results always have a 'pattern'

Companies trying to make their numbers look better than they actually are, or companies with distortions in their business models, strangely possess similar 'patterns'.

Inflating profits through excessive stock-based compensation (SBC). Unnatural gaps between operating profit and cash flow. An abnormal dependence on existing customers, contrary to the 'new acquisition' headlines.

The moment the numbers from Datadog'sIncome Statement (PL)andCash Flow Statement (CF)were lined up, a danger signal rang in my head: 'Ah, this pattern again.' The three minutes were not for calculating the numbers in detail, but for sniffing out this 'scent of typical distortion'.

And just as that sense of unease suggested, lying deep within the primary source was an 'inconvenient truth' that the media had covered up.

1. The truth behind 'rapid growth due to AI demand': 75% of the revenue increase depends not on new customers, but on deepening (expanding) existing customer accounts.

2. The truth about 'cost-free': Behind it lies a massive increase in infrastructure costs paid to cloud providers (an increase of $41.8 million).

3. The truth about 'profitability and abundant cash': They are simply preventing cash outflow by printing and distributing 'stock-based compensation (SBC)' that is about four times their net income (over $200 million).

Do not invest in 'summarized headlines'

What I wanted to convey through this article is not whether 'Datadog's stock is a buy or a sell'.

'How conveniently and beautifully secondary information filtered through the media is processed' is the fact.

'The largest ever,' 'AI champion,' 'Only code is shipped.' These attractive narratives scattered by the media neatly strip away the 'noise' such as the alchemy that severely dilutes the equity of existing shareholders.

You should not invest your precious capital based solely on 'headlines' that someone has summarized to sound pleasant. The work of deciphering SEC filings and grappling with inorganic data where countless numbers are listed is by no means glamorous.

However, only those who have faced hundreds of financial statements and trained their own 'filters for detecting danger' can see through the 'magic trick' that management wanted to hide. When you see spectacular news, that is exactly when you should open the door to primary information with your own hands. There, a cold, hard 'truth' that is far more thrilling than media reports is sure to be waiting.

[Postscript] Why I saw through this company in 'just 3 minutes'

Finally, a little behind-the-scenes story. This time, it actually only took me '3 minutes' to open Datadog's financial statements (primary information) and see that this company is not the 'pure and innocent excellent company' that is being praised in the media.

I didn't punch detailed numbers into a calculator. From my experience of looking at the financial statements of hundreds of companies over many years, I was able to quickly sniff out 'two strange odors' the moment I opened specific pages.

① Stock-based compensation that is '4 times' net income The moment I glanced at the cash flow statement and the statement of changes in equity, the fact that they were printing and distributing their own stock worth about 4 times their net income ($52 million) (i.e., $206 million) jumped out at me. At this point, an alert goes off: 'Oh, they are playing a game of printing stock to keep cash on hand rather than generating profit.'

② The scent of 'financial engineering' visible in the investment division And the deciding factor is the breakdown of the 'investment division (marketable securities)' on the balance sheet. Despite having a huge amount of operating funds of $4.3 billion, less than 20% is in 'US Treasury bonds,' the representative of safe assets. Surprisingly, they were chasing yields by dumping more than half, about $2.4 billion, into 'corporate bonds' that carry credit risk.

True blue-chip companies like Apple or Microsoft would never put together such an aggressive investment portfolio.

The moment I saw these two things, the dots connected for me. 'Ah, this company is a company of advanced money-making (financial engineering) wearing the skin of a pure AI/SaaS company.'

Using their own stock like alchemy to hoard cash, and then further investing it in the corporate bond market to squeeze out returns. The true face of a 'money maker' that is extremely greedy and raw, completely different from the beautiful face of 'only code is shipped' painted by the media, was completely visible through this 3-minute look.

Financial statements are truly interesting, aren't they?

#KatoChanAnalysis

(Disclaimer: This text is for informational purposes only and does not constitute a solicitation for any specific stock, investment advice, or a guarantee of the completeness of financial analysis. Investing involves risk. Please make final investment decisions at your own responsibility.)