Snowflake - What's going on?

I’ve been graphing Snowflake ever since the IPO just to keep it on my radar. I was interested in the company but the price just seemed silly high. It had opened after the IPO at about $245, ran up that day to something like $319, but came back down. The last four weeks I have it closing at $229, $227, $238, $240 (tightly range bound!). I decided this week to take a tiny position to make me pay more attention and made purchases on three different days. The first day I made some truly tiny purchases at $245.50, and one more at $247.50, and ended up with about a 0.12% position (an eighth of a percent). Yesterday I added more at $263 (I tend to buy when the price is going up, but what the heck is going on?), and at $268 this morning (down a little from yesterday’s close), and when I looked at today’s close it was at $297!!! That’s $297!!! And this move was without any news that I could find, and while all the rest of our companies were having a tough week.

I ended up with a 0.65% position and wished I had bought five or ten times as much.

I couldn’t find either a press release or news, except for some analysts setting $300 targets (but I don’t consider that news).

Does anybody on our wonderful board know anything, or suspect something, or have any ideas they’d like to put forward about what hit this stock this week? (Remember that this was a tough week for our stocks in general).




I took a 2% position in SNOW when I sold FSLY.
The recent tech IPOs - SNOW, U, PLTR are all shooting up. Looks like some kind of sector rotation by funds.

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Saul, Glad that you brought this up.

I also took a small position a few weeks back. Initially I wanted to wait for the lock-up period to end but thought about starting a small position.

SNOW is doing a lot of wonderful thinks. I think muji had written some details sometime back.

I’ll post my thoughts in a few days.




Hi, I have noticed that too, the same story is for U, especially Unity revenue growth is at 30 to 40 range but trade at NET and FASLY range.does that mean the valuation for SaaS have to be re-looked at ?


With no notable news in sight for Snowflake, it does seem as if there is a bit of a rotation going on into the newer IPOs.

Over the last week, some cloud darlings have performed as follows:
ZM +2.2%
MDB -7.4%
TWLO -9.1%
DOCU -9.2%
OKTA -11.0%
DDOG -12.9%

Meanwhile, over the same period, the performance of some of the recent IPOs have been:
SNOW +22.2%
U +12.2%
FROG +9.6%
PLTR +3.6%
ASAN +2.9%
SUMO -9.2%

As Saul alluded to, there have been a couple of notable analysts setting ~$300 price targets in the last week. Although this is not news per se, it seems to have had some influence on momentum / algo traders.

Perhaps the market thinks that recent IPOs won’t get as “penalized” as some of the cloud darlings for failing to “beat & raise”? With Q3 earnings coming up, that could be a way to hedge against -20% drops as we’ve seen from AYX and FSLY recently. Alas, this is just me speculating at this point…


My feeling is that too much emphasis is being put on quarterly reports and too little on how these companies execute their long-term strategies. We cannot really see for sure how these new darlings on the block are/will be performing, other than their stock prices going wild.

Apparently a single quarterly report implying anything less than exuberant growth perspectives during this global pandemic is a reason to abandon ship abruptly and completely.

The Foolish thing to do should be to identify great companies you love enough to stick with through thick and thin, with great leadership and long-term growth potential and to build a portfolio reflecting your vision of the future.

What I took from the board so far was mostly that it is a good idea to build a concentrated portfolio (< 15 companies) comprised of your best ideas. I was already able to trim ~30 companies from my portfolio by narrowing this down to my personal favorites, albeit it was and still isn’t easy. I’m down to 16 companies for now.

And I found one new company here to research (NET), liking it more and more. Of course, I am once again late to the party, which tends to be a tendency of mine, owing to my nascent investing career. Since I already got CRWD, I can’t bring myself to add yet another security piece with DDOG that I see around here. And for me, at least for now, NET feels better than betting on SNOW.

SNOW might be great, but I find it very hard to make a judgement on it as of yet. And I am sure until the time I would feel comfortable about owning a meaningful piece of it, it would be priced into the next decade.


Hi RevTK,

I’m pretty new to the board, but not new when it comes down to NET. Followed them since inception, they are just starting to expand aggressively towards enterprise, with last quarter enterprise revenue growth of 65% ! Number of new clients (spending more than $100k) is 11 times more than Fastly, 80 vs 7. They have so far captured only about 16% of the global 2k customers. They are just starting to build a true dedicated enterprise sales team. Expect to see their DBNER rocket past their previous range of 115-117% due to be able to recognize recurring revenue from the past couple of quarters (probably see this in 2021).

Also, DataDog competes primarily with platforms such as New Relic, DT and somewhat with Splunks and Elastic. I wouldn’t consider Datadog a security play. That being said I have Crowdstrike, Okta, Cloudflare as my main security plays and Datadog, Elastic and Splunk as application performance monitoring, log management, etc. The last 3 have security elements SIEM/observability


Does anybody on our wonderful board know anything, or suspect something, or have any ideas they’d like to put forward about what hit this stock this week?

We continue to observe a rotation (within high-growth technology stocks) going into the newer IPOs, some of which have yet to report their first public quarter.

Since October 15, notable Covid winners have performed as follows:
ZM -13%
MDB +3%
TWLO -2%
DOCU -5%
OKTA -2%
DDOG -15%
CRWD +2%

Meanwhile, over the same period, the performance of some of the recent IPOs have been:
SNOW +35%
U +62%
FROG -5%
PLTR +226%
ASAN +20%
SUMO +12%
ZI +19%

That translates to an average of -5% for the “Covid winners” highlighted above, compared to +53% on the new IPOs (a 58% difference!). Even excluding PLTR, the difference is 29%!

While 6-weeks is a very short time-frame from which to draw any notable conclusions, it is also worth paying attention to these trends. We can draw our own inferences to hypothesize on the potential drivers for this - and as time goes by, we can add information to our analysis to iterate on our hypothesis.

For now, we know that:
(1) The “Covid winners” mentioned above underwent pronounced top-line growth + margin expansion this year. All of these companies have undergone triple-digit stock appreciation

(2) Given the low interest-rate environment, and the adverse effect of Covid on many industries, these SaaS companies became a safe-haven for many yield-seeking investors

(3) Seems obvious - but worth remembering that for investors to buy into highly anticipated IPOs, they must either deploy dry powder or sell other positions

It is possible that this is a temporary effect and soon enough, mean reversion will occur. However, it is also possible that these newer IPOs (or upcoming IPOs) provide an opportunity to allocate some capital early and (as always), ruthlessly increase/decrease that amount as management proves us wrong/right.

The reason why I’m highlighting this is because this board emphasizes an open-mindness to evidence that may lead us (individually) to change our investment behavior, and collective challenge our ideas through fruitful discussions. Despite the volatility in tech growth stocks lately, I find this evidence notable enough to note and discuss, so that we can all become better investors.


A lot of money is going into IPO. Plus the money going into stocks of companies depressed by Covid. .Both of these seem like sure gainers in the short term. That money has to come from somewhere. Ken Fisher has written about how IPO can help kill off bull markets. But in this case the IPO are mostly in tech and software so may be depressing only that slice of the market
In the longer run has much changed about the business of our companies? If/when many of the Covid depressed companies recover they will have to accelerate their shift from just conserving cash and avoiding bankruptcy to digital transformation. And as our favorites grow in sales but stay the same or get a bit lower in price they increasingly become more attractive for a sector shift back to them. That being said I think the"easy" money in a SaaS been made, everybody must know about it now. Why I am trying to look elsewhere for new investments. Without much luck so far.


My observation is that of the IPO list, only 3 have reported even once. U, ZI, and FROG.

(We cannot invest for business performance until we see business performance.)


Hi rmtzp

Thanks for the post.

I have noticed the same given that I have maintained core positions in the usual suspects including: Shopify, TTD, MDB, Datadog, Crowdstrike, Zoom and even Alteryx, I have exited Hubspot and Okta as well as Smartsheets, Guardant Health, Invitae and Exact and top sliced TTD and MDB in order to invest in some starter positions in some of these newer names (EXPI, SEA, Digital Turbine, JAMF, Ontrack, Magnite and Farfetch) as well as some recent IPOs (Asana, Snowflake, Palantir and Ncno).

With the exception of Snowflake all of the recent IPOs were very slow out of the gate. Traditionally the IPO season has always been Q2 and Q4 so I am not surprised that IPO investment money took till Q4 to really take off and Q3 was out of season and Q2 disrupted by Covid.

Of course we are also passed the election so to a degree an amount of uncertainty has been removed and we know that traditionally election years produce strong returns in particular going to year end.

I find the Covid rotation very short termist. In the recent plunge I actually took the opportunity to top up on Zoom and Datadog - 2 of the most covid WFH exposed stocks.

In the longer term, I feel that high growth high quality SaaS plays will continue to deliver in the longer run just as the overhaul of traditional industrial stocks by the new economy mega-corps took decades to play out. I also do feel that the recent IPO/emergent plays were both unknown and probably undervalued potentially due to a lack of transparency, track record and conviction in prospects. As they establish their records I suspect this will change.



Following up on my last reply…and happy weekend!

Allow me to call this “Snowflake Demystified”

As tech companies are solving unique problems at the right time, the definition of the cloud is also evolving. So, you can think about three layers of cloud like…

Cloud Infrastructure: ( Azure, AWS, GCP)
Cloud Database/ Data Cloud: (??)
Cloud Applications/Services:( e.g. all SaaS companies like CRWD, CRM, DDOG, DOCU etc)

Well, Snowflake fits in that Cloud Database layer. Snowflake is build for the cloud and is built for performance, sclability and security of data. BUT, there’s a BIG difference. You won’t find many names in that Data Cloud bucket.

So the picture today is more like this…

Cloud Infrastructure: ( Azure, AWS, GCP)
Cloud Database/ Data Cloud: ( Only SNOW)
Cloud Applications/Services: ( e.g. all SaaS companies like CRWD, CRM, DDOG etc)

Just a few years back, I worked extensively with big data and was quite proficient in extracting, transforming and loading data ( also known as ETL). I used my skills to create metrics and data reports that were being used to drive new feature development and A/B testing at my company and also measuring the success of the business ( like calculations of DAU, MAU, ARPU, LTV etc). It was super-easy for me as I was a domain expert and worked in my own silo.

However, if you asked me to work with datasets from disparate sources, the complexity of my work would multiply many times. And if that data happened to reside in different public cloud providers, I would almost give up!

So, if someone came with a magic wand and told me that I don’t need to worry about where the data originates from and can just use that data and analyze it as if it resided in just one place; it would indeed be magical! Well, that’s exactly what Snowflake is doing. It helps Data Engineers and Data Analysts to do their job without the need of worrying about actually where the data originates from.

For the benefit of my non-techie friends, I’ll try my best to explain this without any tech jargon in it’s simplest form.

…Say your application is generating raw data like who’s using your service, how much time they are on it, what platform they’re on (iOS, Android, Windows), how much they are spending etc ( all stored as events in a AWS S3 bucket). You simply load that data into a Snowflake instance ( think of this as your Snowflake Cloud database and some virtual warehouses to process that data. Once the data is processed you can now use a BI tool to build reports and analyze that data.

The power and beauty of Snowflake is that you can simply do the above operations for data residing anywhere ( AWS, Azure, Google Cloud). Snowflake works with both structured and semi-structured data ( like JSON) very easily.

So, that’s basically what Snowflake does. What’s unique is that, no one else does that stuff better than them as of today and their pricing is pay only when you use. ( If I were on the Snowflakes sales team, that would be my sales pitch to Mr.Buffett :))

And Snowflake uses standard ANSI SQL, which most Data Engineers/ Analysts are familiar with and it makes their work easy. Snowflake also handles all indexing and partitioning automatically. Their multi-clustered shared data architecture allows data to be analyzed as it’s loading which is really cool.

If you haven’t heard about this, Snowflake has a Data Marketplace for sharing data. A good example is the Starchema dataset and Weathersource which helps relate COVID-19 data with the impact of Weather. AFAIK, This data has been requested by more than 2000 Snowflake customers. And you could also use datasets like Factset and numerous other data providers that make their data available on Snowflake Data Marketplace along with your own business data to build insights.

I won’t go into more tech details but would like to mention that Bob Muglia, the former CEO of Snowflake was a member of my leadership team at MSFT and I have great respect for him.

As mentioned in the previous post of this thread, I bought my first position of SNOW just after the IPO at around $240 and it’s up 61% as of today ( not too bad :)).

I won’t be selling my SNOW shares unless I see a competitor come up with a better solution. Right now I don’t see any on the horizon. This also somewhat explains why their net revenue retention rate is 162%.

As someone rightly said “data is the new oil” and I say “you need refineries to process that crude into more useful products”. That’s what SNOW does with all that data. I may keep adding on dips as it’s currently sitting at the bottom of my portfolio at around 5% ( after the 61% rise).

Hope you find this helpful!




P.S. Please understand that it’s very hard for me to express my thoughts without bringing in technical jargon but for the benefit of all users in this board. I’ve tried to explain what Snowflake does in very simple language. Email me if you’ve any technical queries and I’ll try to find time to answer them if my daily job permits :slight_smile:

I created my twitter account @algocodetest today out of curiosity after seeing many in the twitter community caught off-guard with Snowflake’s ascent. I won’t be posting much there ( as I’m very much time constrained).


The only other thing I would add is that you only pay for a really powerful server when you are needing all of that power. One of the problems of prior solutions is/was that when you need to ingest a huge amount of data and carve it up into more useful pieces of data for the analysis tool(s), you need a fast, powerful server with a lot of storage. (Otherwise sales managers complain that they cannot see last month’s sales data in their fancy reporting tools until the current month is 10% “over”.)

The rest of the “month” or week, you only need a bunch of storage, because the reporting tools don’t require nearly as much horsepower.

By putting your solution out on a “shared” mega-server, you pay for the horsepower only when you use the horsepower, you pay for the storage (all the time)…

AND in really detail-oriented corporations, these expenses are quite distinct and allocate-able to proper departments.


You won’t find many names in that Data Cloud bucket.

Seems to me that there are bunch of companies in the Cloud Database area, not the least of which is MongoDB.


Seems to me that there are bunch of companies in the Cloud Database area, not the least of which is MongoDB.

Amazon’s RedShift and Google’s BigQuery are the more direct competition to Snowflake.

As I posted about a week ago, I am worried about MDB long term. At my previous company, we used Amazon S3 as the IoT data gatherer and then fed from that into RedShift in batches. We ran most of our analytics on RedShift Snowflake could easily replace RedShift in that workflow.


Good explanation, ronjob.

I used to be a Data Architect, so designing datamarts, data warehouses, and other data structures for analytics was my job. Building a data warehouse is a complex and expensive endeavor. As rtichy points out, you need massive compute power and vast storage capacity available to handle the analytics. The problem is that capacity is used a fairly insignificant amount of time; the vast majority of the time, it sits idle. So, the cost per minute utilized is IMMENSE.

Not only are there significant hardware requirements, the human capital required is also large. At minumum, you will need Highly Trained, Expensive Humans (HTEHs) to design and maintain the hardware stack, another HTEH to design the data structures, and yet another HTEH to build the software to extract, transform, and load (ETL) data from other systems into your data warehouse. And yet more HTEHs to write the queries and perform the analysis.

Now, there is SNOW. Organizations that use SNOW have none of the hardware requirements (and the HTEHs needed to design and maintain them). They need someone to help with the ETL, and they need someone to do the analysis. So, the cost of data analysis drops dramatically. Most data is sourced from applications like ERP systems or CRM systems. Modern versions of these application usually provide easy extraction of data in a format that is SNOW-ready, so the BI analyst can often do a significant portion of the ETL without having to involve IT.

How does SNOW work? When an analyst is ready to dig into a data problem, either he/she can extract the data themselves, or enlist a software engineer to help. Once the core data is extracted, the analyst will log into SNOW, choose the right size of instance based upon the size of the data set, and upload the data. Once that is done, the clock starts and the company will be billed for the storage and compute resources used during the analytics. When the analyst is satisfied, either the instance can be deleted (and the clock stops), or the data can remain in SNOW but the compute resources released until needed again. Data and compute resources are billed separately, and metered based upon actual usage. I watched a demo video, and for small BI tasks, where the analyst is in and out fairly quickly, the cost is less than a cup of coffee.

THAT is the kind of power, flexibility, convenience, and cost savings that will embed SNOW in many, organizations. Those newer to BI will never need anything else. Firms with mature use of BI will be able to scale back their in-house infrastructure and staffing as analysts rely on SNOW. They will be able to do MORE analytics on a smaller spend.

I am excited about the future of SNOW. I wouldn’t call it a Cloud Database company at all, although certainly it has database services. It is a Data Analytics as a Service company. MongoDB is a cloud database company. Oracle is a cloud database company (or aspires to be). Snowflake is a analytics platform.

I personally am waiting for the lockup period to expire and a quarterly report issued before I buy shares. It is (IMO) too richly priced right now. I suspect that it will get a haircut early 2021, but I have been wrong before on such companies. SNOW is a game-changer in a very large and growing part of corporate spend. Its user base will be various administrative offices, not IT. The “Land and Expand” model will drive growth for years.

Tiptree, Fool One guide and IT geek.


Thanks TMFTiptree and Ronjob, you guys are really great. I agree that I want this company to come down, but maybe I won’t see that. If Ronjob is correct and nobody competes with them than they have the field all to themselves. Do you know of anyone that competes with them TMFTiptree?


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Really great post from both ronjonb and Tiptree, that’s how I feel about SNOW as well
Just want to add one more, from their CC , they started to support unstructured data as well , video, pictures,social media, PDF ,building the foundation for Machine learning .

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Most data is sourced from applications like ERP systems or CRM systems.

While that used to be true, and those workflows still exist, in today’s world it’s IoT data that taxing existing systems and impacting almost everything. Instead of just records for each customer, you’ve now got things like part and assembly records from the manufacturing floor. For instance, the automotive companies I’ve worked at all use connected torque wrenches so they have a record of the tightening torque for every important bolt of every vehicle. Heck, even torque wrench recalibrations are recorded in the database.

One of the more promising use cases is around product defects. As customers report problems, you can run analytics on them to look for patterns on the manufacturing side and then preemptively contact customers who haven’t yet reported problems but are likely to experience them. Automotive OEMs use this to save millions of dollars in being able to narrowly select which vehicles are subject to a recall.

And even if you’re not a manufacturing company, your user records now often expand into things like mobile application use. Your customer’s data isn’t just a single record of their purchase anymore, there’s literally a record for every use of your product (physical or software) by that customer.

To top it off, AI is starting to become usable by mortals in more applications, helping to pull actionable information out of the explosion of data being handled and stored.

This is a big challenge for organizations. This article is a few years old (… ) but is a pretty good explanation of the basics for laymen. Compare the data in that to this more recent data from Kaspersky:…

• 61% of organizations across the board are currently using IoT platforms in their business
• That’s up 5% - 10% since just last year! (and without hardly any 5G, lol)
• A third of companies give third parties access to their data!

The growth in IoT is pretty amazing, especially when you consider the report is dated March 2020 so doesn’t take any Covid accelerations into account.

And while Kaspersky is focused on the security aspects of third party data access, for Snowflake this trend ties into their “Data Marketplace” offering (as mentioned by ronjob). I initially didn’t see this as anything major from Snowflake until the realization that 1/3 of all companies are sharing data.

To summarize, IoT is creating orders of magnitude more data than traditional ERP and CRM use cases ever had. This means it’s less likely that customers will look to on-premise solutions, and that cloud-based solutions are more appealing from cost and convenience.

I wouldn’t call it a Cloud Database company at all…

Sure. Here’s how Snowflake describes themselves:

Snowflake is an analytic data warehouse provided as Software-as-a-Service (SaaS). Snowflake provides a data warehouse that is faster, easier to use, and far more flexible than traditional data warehouse offerings.…

To help non-technical people understand the differences, while both can store data in the cloud:
• Cloud Database is often used for OLTP (OnLine Transaction Processing), with Report Generation.
• Cloud Data Warehouse organizes large amounts of data for efficient Analytics.

The difference between Report Generation and Analytics can be hard to understand at first. Basically, Report Generation is a straight forward process. A report might contain how many widgets your factory built each day, or how many widgets were sold, or how many problem tickets were filed. Analytics involves a deeper dive, often pulling data from different sources and finding non-obvious correlations that provide useful insight or actionable data.

As examples, a Report would tell you how many widgets were sold each week in each region. Analytics could tell you how your advertising campaigns in different regions over time affected sales in those regions, or which advertising campaigns were most successful, or whether certain campaigns were more effective in some regions and less effective in other regions.

As for MDB and Oracle, both claim to support analytics workflows, and they do for some more limited sets of data. One of the beauties of Snowflake is that it supports both structured and unstructured data, whereas something like MDB only supports unstructured and Oracles mostly relational databases only support structured data.

Snowflake is a analytics platform.

Yes, that’s it’s main advantage. A while back here people were wondering about competition between analytics companies like Alteryx and Talend against Snowflake. Both companies provide connectors to Snowflake: see and . I don’t view them as competing with Snowflake, but rather enabling them to have their data hosted wherever they want, including on Snowflake. For its part, Talend has put together a PDF of various articles on the benefits of cloud data warehousing that’s worth a read if you want more technical details:…

That said, it’ll be interesting to see if Snowflake eventually expands into providing actual analytics services themselves. Right now it appears to be all third parties ( ), but that might change if Snowflake decides that being frenemies is OK once they’ve more fully established themselves.



Their chief competitors are AWS and Google Cloud. AWS offers a data analytics service called Redshift, and Google offers BigQuery. The competitive advantage that SNOW offers is apparently ease of use, cost, and being cloud-provider agnostic.

Hope that helps!

Tiptree, Fool One guide, long AMZN and GOOG