Datadog Named a Leader in the 2022 Gartner Magic Quadrant for APM and Observability $DDOG
Industry analyst Gartner just released their 2022 Magic Quadrant for Application Performance Monitoring and Observability. These reports are important because they are consumed by enterprise IT decision makers as an input to technology purchase decisions. They provide a directionally useful measure of a provider's position in a product market and how its offering relates to competitors.
If you aren't familiar with the format, Gartner rates providers in a technology segment along two criteria - ability to execute and completeness of vision. The former measures the go-to-market motion, including items like sales execution, pricing, financial position, marketing effectiveness and customer experience. Completeness of vision is forward facing, measuring product strategy, business model, innovation and marketing communications. Each provider is assigned a score for each criteria. These are then graphed in a two-dimensional grid with four quadrants. The most desirable quadrant is of course furthest up and to the right, called the Leaders Quadrant.
Beyond assessing a provider's absolute position on the grid, I also find it illustrative to compare their current position with that from the prior year. Movement down or to the left represents a loss of market share or product innovation. Over time, legacy players tend to migrate to the lower left quadrant, charitably called "niche players".
Gartner defines the market segment as "software that enables the observation and analysis of application health, performance and user experience. The targeted roles are IT operations, site reliability engineers, cloud and platform ops, application developers, and product owners." Interestingly, Gartner expanded the title of this year's report to include the word "observability". The context here is that observability adds meaning and explanation to monitoring data. It also implies that leading tools employ AI-augmented analytics to quickly identify or even predict issues, based on the underlying telemetry signals collected. Leading providers have incorporated this "intelligence" into their toolset.
In terms of the results, Datadog was assigned to the Leaders Quadrant for the second year in a row. Further, they were scored highest on the Ability to Execute and second highest in Completeness of Vision, just behind Dynatrace. While one might infer that Datadog is behind Dynatrace, the important consideration is the relative velocity of Datadog's move from year to year. Datadog has been rapidly ascending the diagonal line up and to the right over the last 2 years. In 2020, Datadog wasn't even in the Leaders Quadrant, just making it into Visionaries. In 2021, they crossed into the lower corner of the Leaders Quadrant. Now, they are tied with Dynatrace for furthest up and to the right. Over the same timeframe, Dynatrace has largely remained in the same position.
Other competitors aren't even close. New Relic has remained in a distant third, maintaining the same relative position for 3 years in a row. Splunk and Elastic remained in the Visionary segment, with some movement up and right. IBM ascended into the lower end of the Leaders quadrant after the acquisition of Instana. One company to watch is Honeycomb, who landed in the Leaders quadrant for inaugural entry. Legacy solutions faded as we would expect including Broadcom, Oracle and Cisco AppDynamics.
I plotted Datadog's trajectory over the last 2 years using the green line, with small dots representing their absolute position in 2020 and 2021. Their gains in position were the largest of any vendor. I think this reflects Datadog's strong product development motion, in which they launch new product offerings and flesh them out quickly. We should keep in mind that Datadog introduced their APM offering in 2017, after only offering infrastructure monitoring for their first 5 years. Competitors have had an APM solution in market for much longer.
The Gartner report highlighted several strengths in Datadog's offering. They commended the broad platform approach, with a unified and integrated experience. Gartner also called out Datadog's AI-enhanced analytics solution. Watchdog provides proactive alerts and automated root cause analysis. Finally, they noted Datadog's strength in funnel analysis through real user monitoring (RUM). This allows operators to understand complex user behavior across product journeys, identifying churn and drop-off rates.
In terms of room for improvement, Gartner noted that some clients expressed frustration in pricing terms and limited discounting. They also pointed out that Datadog's deployment model is only SaaS based and is not available as a download for customers to run themselves.
All in all, I thought the Gartner report underscored Datadog's continued product innovation. Their competitive position improves every year, demonstrating the outcome of Datadog's robust product innovation. As we consider the report for next year, I expect Datadog to move even further ahead of competitive offerings.
@growthinvesting I have used Splunk in the past for log analysis and it performs reasonable job. They have added APM and other observability tools through bolt-on acquisitions. The experience isn't fully integrated. With that said, their cloud migration is finally gaining traction and they appear to be at a tipping point. They also have deep enterprise penetration. But, they aren't innovating as quickly as Datadog, so I think they will always lag.
Have big stock market winners in the past consistently lead the gartners quadrant?
@irish That's a great question. I find that the Gartner MQ rankings are a lagging indicator. They often keep legacy vendors in the top quadrant longer than they should. Positioning can also become political, as some providers maintain marketing functions that try to game these industry rankings. On the flip side, some great technology companies don't actively participate in these surveys, so they are left out, causing some confusion.
So, I think these industry reports are useful directionally, but I wouldn't make a stock purchase based on the rankings. That's why I like to watch relative movements year to year, like Datadog's trajectory, versus the absolute position in any year.