Datadog, Inc.
Datadog, Inc. operates an observability and security platform for cloud applications in the United States and internationally. The company's products comprise infrastructure and application performance monitoring, log management, observability pipelines, synthetics, real user monitoring, product analytics, continuous profiler, database monitoring, data observability, LLM observability, error tracking, network monitoring, incident response, workflow automation and App builder, event management, bits AI SRE, cloud cost management, cloud security, code security, cloud SIEM, threat management, sensitive data scanner, and CI visibility. Datadog, Inc. was incorporated in 2010 and is headquartered in New York, New York.
What does it do?
Datadog is like a control room for companies that run their software in the cloud. Imagine you work at a bank and your app suddenly slows down — Datadog tells your engineers exactly where the problem is, in real time, before customers start complaining. It monitors everything from servers and databases to how fast individual web pages load for real users. Companies like Airbnb, Samsung, and Peloton all use Datadog to keep their digital products running smoothly.
As businesses move more of their operations to the cloud, the complexity of keeping everything working grows exponentially — and Datadog sits right in the middle of that problem. The rise of AI is making this even more urgent, because AI applications are expensive to run and hard to debug, and Datadog has built specific tools to monitor them. Investors see Datadog as a picks-and-shovels play on the cloud and AI boom — meaning it benefits regardless of which AI model or cloud provider wins.
How does it make money?
Datadog makes almost all of its money through subscriptions — customers pay monthly or annually based on how much data they send through the platform. Revenue hit $3.4 billion in the latest fiscal year, up from $2.7 billion the prior year, a growth rate of roughly 26%. The more cloud infrastructure a customer runs, the more they pay, so Datadog's revenue naturally grows as its customers grow. It also benefits from customers adding new modules — like security monitoring or AI observability — on top of their existing subscriptions.
Why do investors care?
The core growth story is simple: cloud spending keeps rising, and every dollar spent on cloud infrastructure creates demand for monitoring tools like Datadog. The AI angle is newer and potentially bigger — every company building an AI product needs to monitor it, and Datadog launched LLM observability tools to capture that spending. For the thesis to work, Datadog needs to keep winning large enterprise customers and convincing existing ones to buy more modules over time. The risk is that net income is still only around $100 million on $3.4 billion in revenue, so the company needs continued growth to justify its $82 billion valuation.
Deep Dive
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