509d3f81-5ab0-47d8-b044-88c293b4f7b5_Datadog-Premium-Research.pdf
Datadog Premium Research
Fundamentals
Following its IPO in September, Datadog reported revenue that was up 87.8% year-over-year at $95.9 million compared to analyst expectations of $87.73 million. The revenue growth was higher than the 79.5% reported earlier in the year.
Company guidance for Q4 revenue is between $101 million and $103 million. Full year revenue is expected to be between $350 million and $352 million. Forward 1-year revenue is expected to be around the $500 million mark.
This places Datadog second to Crowdstrike for estimated forward revenue growth in the cloud software category.
However, it bears mentioning, Datadog is closer to profitability than any other cloud software company (among those currently reporting negative EPS). Datadog hovers near profitability with non-GAAP operating margin of 0.7% and non-GAAP EBIT of $0.6 million. GAAP operating margin is negative -4.4%. Free cash flow is negative $3.7 million.
Full year non-GAAP EPS is estimated at negative -$0.12 to -$0.11.
Datadog went public in September and is trading at 34 times the midpoint on its full-year guidance of $351 million. If other IPOs in 2019 are any indication, the expiration of the lock-up period on March 17th will likely see some level of adjustment in valuation.
Addressable Market
The broad infrastructure monitoring market is quite nuanced with many players specializing in various aspects of cloud and IT. The broad addressable market will be worth $34 billion by 2024. It requires further effort, however, to break this down into the areas that Datadog directly serves.
According to IDC, the global APM market reached $4.3 billion in 2018, posting 13.4% growth from 2017. The fastest growing companies during 2018 was AppDynamics at 42% market share and New Relic at 35% market share. The market is expected to grow annually by 11.84% over the next several years.
Datadog is expanding into network performance monitoring with a current addressable market of $2 billion. The log management market (as a standalone) is worth $1 billion.
Conservatively, Datadog’s addressable market is around $8 billion to $10 billion. For optimists, (such as the Jefferies’ analyst who stated Elastic’s market was around $40 billion), you could look at the $34 billion IT infrastructure monitoring market especially since Datadog does help monitor on-premise.
The $8-$10 billion market is sufficient enough for Datadog to continue its 65% growth with current revenue of $350 million. The company would only have to claim 5-10% of the market to be a breakout stock.
Product Overview
Datadog is a cloud-based monitoring and analytics company that offers infrastructure monitoring and has expanded into application performance monitoring (APM). The company aggregates metrics and events across the full infrastructure and application stack for a single point of view.
Datadog began as an infrastructure monitoring tool in 2010 and expanded into APM in 2016 with the public release in February of 2017 for full stack observability.
Application performance monitoring assures applications and websites run as expected with optimal speeds across mobile platforms, cloud-native infrastructures, virtualized and containerized servers, etcetera. APM also assures that the application is performing as it should, backend processes are executing as they should, including transaction processing, and detects bug or errors in the application code, in the application server, website front end, a slow query, or a slow network.
Distributed application environments can cause numerous bottlenecks and it can be challenging to figure where the bottleneck is coming from. Meanwhile, slow speeds can cause customer drop-off.
APM performs the following functions:
• Digital user experience monitoring: determines if there is slowness, errors or downtime that could lead to a loss of revenue
• Transaction profiling: analyzes the transaction flow to isolate the cause
• Code-level diagnostics: According to DZone, 43% of application performance issues come from code. Diagnostics help to identify the line of code or query causing the issue.
• Deep-dive analysis: Looks beyond code at the server and application infrastructure for problems such as insufficient memory or long wait times
• Infrastructure monitoring: similar to deep drive analysis, ideally infrastructure monitoring is part of the APM package to monitor slow network connections or virtualization bottlenecks.
Competitors
There are a few 800-lb gorillas in the space, such as New Relic, AppDynamics (Cisco) and CA Technologies owned by Broadcom. Dynatrace is also considered a leader in APM and is a private company.
Datadog lists New Relic, AppDynamics and Dynatrace as their main competitors.
Source: IDC APM Market
New Relic
New Relic was founded in 2008 and entered the market with a SaaS-only APM solution. The products have expanded since then to include Infrastructure, Synthetics, Browser, Mobile and Insights for analytics.
The company has expanded into monitoring Kubernetes containers and microservices monitoring (important for automation and machine learning) and now has a presence in Europe although global geographic coverage is a weakness for New Relic. Another weakness is the lack of on-premise.
New Relic’s most recent acquisition was SignifiAI for incident management, which occurred in February 2019. The company is also focused on root cause analysis including predictive anamoly detection, topology-enhanced operational event correlation, and automatic deployment tracking.
Annual revenue of $479 million is expected to grow to $591 million revenue in the current fiscal year ending in March. Forward 1-year revenue is estimated at $693 million. New Relic is distinguished by its profitability, with EPS of $0.24 in the last quarter and current fiscal EPS of $0.64.
App Dynamics
AppDynamics offers both on-premise and SaaS-based APM. Cisco bought AppDynamics for $3.7 billion. According to Gartner, App Dynamics revenue is in the $500 million range+ from sales of APM suites in 2018 (this matches IDC’s data). In an effort to improve its machine learning capabilities, Cisco acquired Perspica in 2017 for a purchase price of $3.7 billion. Perspica helps to surface issues by applying machine learning to large amounts of operations data. Instead of analyzing data after it’s in the database, this helps to analyze the data real-time as it’s being ingested.
AppDynamics weakness is also its strength: Cisco. The revenue is likely reflective of Cisco’s market dominance in networking, yet many APM-specific customers are more apt to go with a smaller, specialized company that is solely focused on APM.
Dynatrace
Dynatrace’s analytics are sold as a package rather than as separate modules with analytics offering real-time topology and AI algorithms to detect anomalies, business impact and root cause across users, applications and infrastructure. The product roadmap includes expanding into multi-cloud and hybrid cloud and using purposebuilt AI to perform root cause analysis faster.
Dynatrace is a premium solution and is priced higher than other APM products.
Catalysts
Hybrid Cloud
I’ve covered the strengths of hybrid cloud in-depth with my Microsoft coverage over the past 1-2 years. Essentially, hybrid cloud allows companies to keep their most sensitive data on-premise while sending less sensitive workloads to the cloud for real-time data processing. Microsoft’s lead in hybrid cloud is what caused me to predict the Pentagon would choose Microsoft over Amazon, as well as Azure’s ongoing growth despite AWSdominance, as Amazon has been focused on cloud-only while ignoring the needs of Fortune 500 companies and others who are more cautious with intellectual property and first-party data.
Read my analysis on Microsoft being a hybrid clod leader here and why this is an important cloud market.
Datadog serves hybrid cloud customers and allows for monitoring of both environments. New Relic, on other hand, is SaaS-only (or cloud only). From my perspective, the most growth will come from hybrid over the next few years as the majority of companies today have resisted sending data to another company’s servers and must eventually choose a solution to remain competitive on AI and ML.
In my opinion, the future growth of hybrid is an important catalyst and market opportunity for Datadog. You can read more about Datadog’s hybrid offering here.
Network Performance Monitoring
Network performance monitoring is a potential catalyst for Datadog in 2020. Although the addressable market is quite small at around $2.1 billion, the cross-selling with customers could strengthen Datadog’s revenue growth.
The company launched network performance monitoring in November of 2019 to expand on infrastructure monitoring and application monitoring. By monitoring virtualized networks, the product helps to increase performance optimization and reduce costs by looking for more optimized network patterns and to quickly find the source for network issues.
For instance, if a cluster is saturating the network capacity, this monitoring tool helps to pinpoint the root cause. There are also topology and traffic flow tools to visualize network connections.
Competitors in network performance monitoring include Netscout, Riverbed, Viavi and Extra Hop. Again, it’s about the cross-selling with the other products that Datadog provides rather than competing in network performance monitoring as a standalone product.
Technical Analysis
By Knox Ridley
Like many new IPOs, Datadog (DDOG), with just 4 months of price action to analyze, is showing a series of overlapping, corrective patterns, signaling uncertainty by the market.
In November of 2019, Datadog hit an all-time high of $44, just before a near 25% drawdown took it down to $33.15. Since bottoming, it’s been in an overlapping uptrend, attempting to repair the damage done.
Using basic Technical Analysis, we have a clear picture of where DDOG is, and what hurdles it needs to clear to regain higher prices. Starting with the upward trend lines that are highlighted in the blue, we can see a clear trend in price that is supported by a rising MACD and RSI. In other words, the momentum is building with price, which indicates a healthy trend. If we see a break of these trend lines in unison, expect Datadog’s price to test the recent low around $33.
If we see these trendlines broken, the red retrace levels offer likely targets, based on basic rules of symmetry and Fibonacci levels. My main target will be around the $31 region if this scenario unfolds, which coincides with the
78.6% retrace level and the 100% extension of the initial move down. However, we could see it bottom at the 61.6% retrace level around $33, or to hit the 127.2% extension around $29-$28. This is my justification of the yellow target box, which I will watch closely if DDOG fails to breakout.
Just above Datadog’s current price is a heavy clusters of Fibonacci prices that coincide with the $40-$42 region. With momentum fading, shown in the declining RSI and MACD, as well as negative divergence between price and the RSI, the probability of Datadog breaking this region is low.
However, if this resistance is broken on heavy volume, expect an acceleration in price due to the high level of short interest in the current float, sitting around 25%. As price moves against shorts, especially breaking a region as significant as the $42 price level, they will cover their positions, creating a rush of buying pressure, which in turn, pushes the price higher at a rapid pace.
Elliott Wave – Scenario 1
The above chart offers my primary Elliott Wave count, which suggests another leg down. This would put us in the early stages of the final (C) wave down. The evidence I use to support leaning towards this count is as follows:
– The (B) wave up is slightly overlapping, which is what we see in corrective moves.
– The declining internals in RSI and the MACD recently discussed are fading, and showing divergences as well.
– The heavy concentration of Fibonacci levels around $40-$42.
– The general fact that the market is heavily stretched and due for a correction.
Expect the (C) wave to retest the last low around $33. If this scenario unfolds, my likely target will be around the $31 region, which is a concentration of significant Fibonacci levels and basic symmetry. I will likely be a buyer around the levels outlined in the yellow target box between $33-$28.
Elliott Wave – Scenario 2
This is my alternative game plan, if DDOG can break through the $42 region with heavy volume. If this happens, we will have a clear 5-waves up, which would tilt the probability that we are in a 3rd wave higher. If that is the case, I would likely go long, with tight stops, which I will update if this scenario unfolds.
Please note, Datadog’s lock-up expires March 17th, 2020. We expect to see some price volatility following this date.