Running DDOG through the Antifragile Framework

Greetings Fools,

Using my Anti-fragile framework, I wanted to show how DataDog Energy stacks up.

Barbell Strategy

Mission Statement
“To bring sanity to IT Management”

I really love this mission statement. The co-founders – Olivier Pomel and Alexis Le-Quoc – worked at Wireless Generation – a company focused on helping K-12 teachers. One worked on Developments (building things) and one worked in Operations (making sure the things that have been built actually work).

Think of this as the construction crew and the maintenance crew for a large subway system. It’s vital these two groups talk to each other. But as the cloud is brand new, people are waiting for some issues of standardization and vocabulary to settle in. That’s why DDOG’s mission is so perfect – it is providing that solution.

Simple: Yes
Optionable: Yes
Inspirational: Yes

+2.0 points


High Switching Costs: Datadog has four broad subscription offerings:

Infrastructure: Again, using the subway analogy, this is where you make sure things aren’t falling apart and are going where they need to be. Clients pay $0-$23 per host per month for monitoring, dashboards, integrations, and alerts.
Application Performance Managmeent (APM): Are the trains arriving on-time and travelling at safe speeds. Only, this measures apps, not trains.
Log Management: Look through all the data about when trains arrive and see what lessons can be learned. This is one area where AI and ML take over. Companies can by for 30-day retention of logs for learning.
Synthetics: This is simply the ability to see what it’s like to be a customer of your service. For the subway, it means literally riding the subway. For tech companies, it means running simulations to get an idea for the user experience.

I explain all four because many start off with just one or two, but add more over time. Dollar-based net retention is 146%. This means customers are not only sticking with DDOG, but adding more of these solutions over time.
+2.0 points

Network Effects: The company relies on AI and ML to power its tools. As customer growth has been off the charts, this is very strong. Additionally, the team at DDOG has built a lot of its tools by observing where clients have unnecessary friction. As one of the few fully funcitoning all-in-one suites, this additional data makes the service more valuable by offering up more insights that other companies don’t have.

+1.5 points

Here’s where I see things getting very interesting. DataDog started with just Infrastructure, and has moved onto its four key offerings. If you think it will stand pat with that, you’re crazy.

Right now, it has over 350 integrations. So if you’re using PagerDuty, for instance, it can integrate its data into DataDog. I wouldn’t be surprised, however, to see DataDog move into other areas it’s not currently covering over time. It has access to all this data, and if it can offer companies the same service under one umbrella, why wouldn’t it.

In some ways, DataDog’s all-in-one mode makes it somewhat like Amazon. Vendors go to AMZN because of the number of clients they are exposed to. But Amazon can undercut them by taking data on sales and developing their own product. DataDog can do the same. Other SaaS need to offer integrations with DDOG’s growing client list. But the very inclusion of that integration also makes them vulnerable to DDOG.

+3.0 points

Skin in the game

Role of founder: Aforementioned co-founders are CEO and CTO, respectively.
+1 point

Insider Holdings Insiders combined own 29.7% of shares outstanding
+1 points

Glassdoor: The company has a 3.8 star rating (out of 5) with Pomel having an 85% approval rating
+0.0 point

Financial Fortitude

Financial statements
Cash: $664 million
Free Cash Flow: ($13 million)

I’m not taking a point away here. Why? Because the company has already proven it can be FCF positive (generated $6M in 2017) and it has no long-term debt. I believe it some type of crisis hit, it could actually take advantage of the situation.

-0.0 points

Concentration Risk
-0 points

Total Score: 10.5 points

This is a very good score. I’m not too concerned about valuation at this point, as I’ll likely be buying a small tranche of shares and adding more over time.

In the end, the optionality of adding more services and using data collected via integrations is very interesting to me. Obviously, with dollar-retention rates like this, there’s a lot going right here. It’ll be interesting to see how the now-very-crowded SaaS field consolidates under fewer umbrellas. I think DDOG could be one of those umbrellas.

See all my holdings here:

What is Antifragile framework and how has it performed?

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Thanks Brian (Cheesehead), you said it so much more elegantly than I did. A very nice analysis. It was greatly appreciated.


I’m sorry, I forgot to ask, what percentage of companies that you test fest a score of 10.5 or better? That would be an important data point.

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“I explain all four because many start off with just one or two, but add more over time. Dollar-based net retention is 146%. This means customers are not only sticking with DDOG, but adding more of these solutions over time.”

Just a note. A large chunk of this dollar-based net retention is natural client growth. Companies that use DDOG growing in size (hosts), not just adding services. For a company like Data Dog, this would be a significant piece to this. If a company has 100 hosts year 1 and that grows to 120, that’s 20% growth right there. With the current explosion of data and such… Lets just say I like the potential.



Great point.


I’ll look into numbers later tonight when I get a chance. Suffice to say it’s a high score. And the absolute numbers aren’t as important as the data that’s laid out to support them.



Appreciate the post. Predictably, here’s a “this is fine as far as it goes, but…” post.
This is fine as far as it goes, but: For some competitors, to really do a solid competitive “moat” analysis, here are some suggestions:
Splunk, Solarwinds, New Relic, Dynatrace - and the big dog that is not publicly traded, BMC Software which is one of the gorillas in the room in this space. BMC’s share of the market and their tools need to be accounted for.
There are several other competitors or just alternatives in this system monitoring space as well -
AWS Cloudwatch; Microsoft Azure (tools); Oracle Enterprise…
and UILA is an emerging vendor with top-of-class tools (we happen to use them currently.)

(below from Fidelity screener page “growth” tab)

Name	        	                       SPLUNK SOLARWINDS NEW RELIC DYNATRACE
Last Trade	 	                       $119.08	$18.25	$61.52	 $19.04
EPS Growth (Last Qtr vs. Same Qtr Prior Yr)	5.63%	88.89%	-160%	-100%
EPS Growth (TTM vs Prior TTM)	               -36.84%	87.80%	-39.06%	-2500%
EPS Growth (3 Year History)	               -4.94%	--	-19.69%	--
EPS Growth (5 Year Historical)	                20.30%	--	-7.96%	--
EPS Growth (Proj This Q vs. Same Q Prior Yr)	42.37%	17.65%	-26.50%	--
EPS Growth (Proj this Yr vs. Last Yr)	        43.91%	35.83%	-16.52%	--
Forward EPS Long Term Growth (3-5 Yrs)	        33.03%	21.45%	20.00%	44.30%
Revenue Growth (Last Qtr vs. Same Qtr Prior Yr)	33.03%	13.40%	30.30%	24.77%
Revenue Growth (TTM vs. Prior TTM)	        36.11%	11.82%	33.62%	12.17%
Revenue Growth (3 Yrs)	                        39.20%	21.07%	38.26%	2.68%
Revenue Growth (5 Yrs)	                        42.90%	19.96%	49.97%	1.60%
Free Cash Flow (TTM)	                        50.8M	274.2M	44.5M	--
Cash Flow Growth Rate (TTM vs. Prior TTM)	-2.97%	0.20%	-0.38%	2.80%
Cash Flow Growth Rate (3 Yr)	                -4.88%	--	-36.05%	--
Cash Flow Growth Rate (5 Yr)	                25.28%	5.73%	-17.44%	-16.97%
Book Value Growth (5 Yr average)	        14.14%	40.15%	--	--

There are a number of these monitoring software providers out there.


To answer Saul’s question from higher up on this thread:

I’ve probably run about 120 companies through the Antifragile framework. There are a couple of things to know about the scores:

  • I don’t keep an active database of all the scores, though I do keep copies of every write-up.

  • The data that I have to consider is far more important than any numerical value I peg it at.

  • The scores would change if I were constantly updating them, some up – and some down.

  • The 120 companies I have chosen have either been an official David or Tom Gardner pick or one I’m interested (usually thanks to this board), so it is highly skewed toward higher-quality companies.

Of those 120-ish reviews, about 15 to 20 have scores of 10.5 or higher

To the best of my knowledge, this includes, ZM, TWLO, TEAM, OKTA, AMZN, GOOGL, MELI, FB, SHOP, CRM, NEWR.

If you have favorites that aren’t on this list, it might simply be that I haven’t run them through. This is an exercise I do because I think it gives me the biggest bang for my buck – highlighting the most salient points I like to consider before making an investment.

Overall, I’m impressed with DDOG. It’s getting harder and harder for me to see how all these SaaS companies might fit together like a jigsaw puzzle within companies. Overtime, I think we’ll get some super-aggregators that have enough quality offerings that companies are willing to – for example – get the #2 monitoring service, if it’s under the same umbrella as the #1 infrastructure and simulation tool (or something like that).

DDOG is on my list as a stock I’ll likely take a starter position in.

Hope this helps,

Positions here: