Datadog Inc. (DDOG, Financial) is rated by Gartner as a leader in information technology observability solutions. As IT systems become more complex and produce more data, monitoring these systems can be a challenge. In fact, a study by Logic Monitor states that 93% of IT leaders believe observability is a “foundational part” of running a modern company. Despite this importance, only an average of 19% of IT observability services have been automated.
Datadog solves this problem with its cloud monitoring as a service solution. In this discussion, I will break down its business model, financials and valuation. Let’s dive in.
IT business model
Datadog offers a unified view of all a system's metrics, from application performance to latency and the cloud. Its main solutions can be divided into the following:
- Infrastructure monitoring
- Network performance monitoring
- Network device monitoring
- Container monitoring
- Serverless
- Database monitoring
- Data stream monitoring
The company also offers security management for the cloud and applications, which has become a vital part of the tech stack.
Digital experience is also an interesting and important area. DataDog offers real-time user monitoring for both desktop and mobile, as well as “session replay,” which enables customers to capture and replay a user's web browsing experience. This is ideal for customer journey tracking and solving user interface issues.
New AI features
DataDog introduced a number of new artificial intelligence features at the DASH user conference in August. They included a large language model observability product, which enables machine learning engineers to deploy and manage models in production. The engineers can easily monitor model performance and identify drift, which tends to occur over time.
The business also introduced Bits AI, a generative AI query tool that enables a user to interact with IT systems using natural language. For example, a user can ask, “Are there any issues with x application?” The tool can even be used for automating tests and incident responses.
Strong second quarter
Datadog reported strong financial results for the second quarter. Its revenue of $509.46 million beat analyst forecasts by $8.45 million and rose by over 25% year over year. This was driven by solid customer growth from 21,200 in the prior-year quarter to 26,100. It was also great to see the business has 2,990 customers with annual recurring revenue of $100,000 or greater. Ironically, these high-ticket customers generated a staggering 85% of its ARR, and therefore it is clear hunting whales makes sense.
Datadog has also adopted a “platform strategy,” which aims to upsell customers multiple products. As of the end of the second quarter, 82% of its customers were using over two products, up from 79% in the prior year. A solid 45% of its customers were using four or more products, up from 37% a year ago, while 21% of its customers used six or more products, up from 14%.
Customer wins
According to its earnings call, Datadog signed an eight-figure deal with a U.S. gaming company, which switched from a legacy vendor. This deal was positioned as a return on investmendriven business with savings of $1 million expected by the company. Datadog also scored a seven-figure deal with a broadcaster who is using Datadog as a way to consolidate its tech stack of five separate tools.
DataDog also scored a major deal with one of the “largest tech companies” in the world. This company has seen huge adoption of its generative AI product and now is in a GPU scaling phase. DataDog is being used to programmatically manage the new IT environments. I believe this acts as a proof of concept for other AI deals that are expected to come online.
Security has been a popular area of increased adoption. As of the end of the second quarter, 5,000 customers purchased security products. Around 79 of these customers spend $100,000 or more on DataDog Security and a few are even spending over $1 million each. I expect the popularity of security products to continue to increase as cybersecurity becomes an even more vital topic, given the rise of AI.
Strong retention
DataDog reported a net retention rate of 120%. This is brilliant as it means customers are sticking with the platform and spending more through upsells.
Billings also rose by a rapid 31% year over year to $520 million. In addition, its remaining performance obligations increased by 42% year over year to $1.25 billion. This is a great sign as these metrics are a strong leading indicator of future revenue.
Margins and balance sheet
Moving on to margins, Datadog reported a super gross margin of 81.3%, with $414 million in gross profit. This is higher than the 80.8% reported in the prior year, driven by improved efficiencies across its cloud infrastructure.
Operating expenses rose by 26% year over year, though the company did moderate its hiring to control costs. Overall operating income rose by $106 million at a 21% operating margin, up from 18% in the prior quarter.
Datadog has a robust balance sheet with $2.2 billion in cash, cash equivalents and short-term investments.
Turning to the balance sheet and cash flow statements, the company ended the quarter with $2.2 billion in cash, cash equivalents and marketable securities. Total debt was $885 million, but the majority was long term and well covered.
Valuation
Datadog trades with a price-sales ratio of 16.39, which is below its five-year average.
Based on historical ratios, past financial performance and analysts' future earnings projections, the GF Value Line indicates a fair value of $248. Thus, the stock is significantly undervalued at the time of writing.
Final thoughts
Datadog is a great company that is truly benefiting from the ongoing digital transformation of enterprises. I believe its competitive advantage is its strong retention and lock-in with customers, which make its solution a vital part of the tech stack. The company has continued to produce strong financial results despite the tough environment. Therefore, I believe it could be a great long-term investment.
