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Datadog sells software that helps companies watch their computers and apps to spot problems before customers notice.
Datadog is a monitoring company for the cloud era. When a business runs its website, apps, and databases across many rented computers in data centers, things break in quiet, confusing ways—a server slows down, a database runs out of room, a payment page takes too long. Datadog's software acts like a giant dashboard and alarm system, pulling in signals from all those machines and showing engineers what's healthy and what's on fire.
The company makes money by charging customers a subscription, mostly based on how much data they send in and how many servers or services they're watching. Its core products track technical performance, scan logs for clues, and alert the right person when something goes wrong. Customers choose it because it plugs into practically everything—Amazon's cloud, Microsoft's, Google's, and hundreds of other tools—and puts one clean view over a mess that used to require a dozen separate products. Datadog was founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, two engineers who met at a previous job and got tired of stitching together monitoring tools by hand. That origin story shaped the product: it's built by people who felt the pain. The bet has paid off. Revenue has climbed fast for years, and the company has expanded beyond basic monitoring into security, log management, and tools for watching how real users experience an app.
Olivier Pomel and Alexis Lê-Quôc had worked together at a company called Wireless Generation, which got bought by NewsCorp. They noticed a basic problem: the people who write software and the people who keep the servers running often pulled in different directions, and nobody could easily see what was actually happening inside the systems. So in New York City they started Datadog, a cloud service that put dashboards, alerts and charts in one place, giving both teams the same view. The idea was simple: less friction, fewer fights, and a clearer picture of what was breaking.
At first Datadog watched over one cloud. Then it opened up to several at once, including AWS, Azure, Google Cloud and Red Hat OpenShift. That mattered because companies were spreading their work across more than one provider, and Datadog could now follow them wherever they went. It was a bet that cloud adoption would keep growing fast, and it put the company right in the path of that wave.
By 2019 Datadog had a choice: sell itself to Cisco for more than 7 billion dollars, or take the riskier road and sell shares to the public. It chose the public road. The company listed on Nasdaq, raised 648 million dollars, and the stock jumped about 37 percent on day one, pushing its value to near 10 billion. Betting on itself had paid off.
Two years later the market went wild for Datadog. The stock hit a record high in late 2021, and the whole company was worth over 61 billion dollars. Here is the striking part: that price was 36 times the revenue Datadog would bring in the following year. Investors were paying for a future that had not arrived yet. Then growth cooled, interest rates rose, and the stock came back down to earth.
In the summer of 2025, Datadog was added to the S&P 500, the index that tracks the biggest public companies in America. It was a stamp of arrival: the little monitoring startup from New York now sat among the corporate giants.
Datadog had always watched over software systems. Now it wanted to watch over data and experiments too. In spring 2025 it bought Metaplane, which checks the quality of data, so it could help data teams and AI workloads. Soon after it bought Eppo, a platform for running experiments and toggling features on and off. Both deals pushed Datadog beyond plain monitoring and into the world of AI and product analytics.
The company had spent years helping humans watch their systems. Now it wanted the systems to watch themselves. Its AI product, Bits AI, passed 10,000 paying customers, and Datadog launched Scout, a model built to power that AI. Analysts at Forrester named Datadog a leader in AIOps, the field of using AI to run operations. The shift was clear: from observability, where people look at the data, toward autonomous operations, where the software acts on its own.
The pullback after the 2021 peak suggested the good times were over. They were not. Datadog's revenue grew about 36 percent year over year, and the growth actually sped up for several quarters in a row. CEO Pomel pointed out that revenue was roughly ten times what it had been at the 2019 IPO. Even customers who were not building AI were growing fast in the high 20s, as they modernized their systems to get ready for AI. Datadog summed up its plan in two phrases: "Datadog for AI" and "AI for Datadog." The monitoring startup had become a business powered by, and built for, the AI era.
The business is sticky. Once engineers wire Datadog into their systems and build their alerts and dashboards around it, ripping it out is painful, so customers tend to stay and spend more over time as they add more services. The risk is competition from cloud providers selling their own cheaper monitoring tools, plus the fact that Datadog's stock is priced for a lot of future growth. It buys back little stock and instead reinvests in new products and occasional acquisitions.
Saved answer · last researched 20 Oct 2026