| Allocations as of | 12/31/22 | 11/30/22 | 10/30/22 | 12/31/21 |
|---|---|---|---|---|
| Snowflake | 25.83% | 25.19% | 25.06% | 12.69% |
| Cloudflare | 20.34% | 21.69% | 22.00% | 13.48% |
| Datadog | 18.19% | 14.29% | 15.60% | 16.60% |
| Bill | 14.70% | 14.68% | 11.56% | |
| Upstart | 11.21% | |||
| ZoomInfo | 11.11% | |||
| MongoDB | 8.85% | 6.72% | 7.08% | |
| Monday.com | 5.49% | 4.72% | 4.82% | 14.39% |
| Crowdstrike | 4.74% | 10.43% | 11.74% | 11.45% |
| Zscaler | 1.84% | 2.25% | 2.14% | 8.99% |
| SentinelOne | 0.03% |
What I learned this month, increasing my confidence in Bill.
Jonwayne wrote here:
This move expands the partnership between CPA.com and Bill.com, CPA.com’s exclusive partner for bill management since 2008, and replaces the previous expense management solution with a new offering that will unite all bill payments, expense management and card spending in one comprehensive solution. A key strategy in supporting CPA.com’s updated client advisory services (CAS) 2.0 framework, firms can now have the technology tools to provide more strategic counsel for clients.
I found this-https://www.officetools.com/blog/client-accounting-advisory-services-are-transforming-the-cpa-world/
There is a definite appetite among businesses for strategic support from the people they trust to help them keep track of their money. in fact, a recent CPA.com study found that, if money were no object
- 68% of clients would want strategic consulting from their CPA firms;
- 41% would even want to turn over some of their financial operations to their CPA firms.
- Bill was again named CPA.com’s exclusive partner (CPA.com is a subsidiary of the American Institute of CPAs, the world’s largest member organization representing the accounting profession.).
What I learned this month, increasing my confidence in MongoDB.
GARTNER MAGIC QUADRANT FOR CLOUD DBMS, DECEMBER 2022
MongoDB-GartnerMQ2022.png.webp
Gartner Magic Quadrant for DBMS, December 2022
After not even being included in the 2021 report, MongoDB landed in the Leaders quadrant in 2022.
“MongoDB received positive feedback from Gartner clients for customer satisfaction. For Gartner Peer Insights, 96% of respondents said they would recommend MongoDB — an extremely strong result that suggests that when used for use cases that are appropriate, MongoDB is an excellent choice.”
GARTNER MAGIC QUADRANT FOR DBMS, DECEMBER 2022
Forrester included MongoDB in their Leader quadrant for Translytical Data Platforms. They excluded the data platform providers that are dedicated to stand-alone analytics and machine learning processing, like the modern data warehouse / lakehouse architectures (Gartners includes these and clutters the field, IMO.)
Translytical platforms are next-generation data platforms that are built on a single database engine to support multiple data types and data models. They are designed to support transactional, operational, and analytical workloads without sacrificing data integrity, performance, and analytics scale. Adoption of these platforms continues to grow strongly to support new and emerging business cases, including real-time integrated insights, scalable microservices, machine learning (ML), streaming analytics, and extreme transaction processing. Translytical data platforms are highly optimized for both reads and writes, leveraging distributed in-memory, multimodel, advanced workload management, AI/ML, and cloud architectures to support modern workloads.
FORRESTER WAVE, TRANSLYTICAL DATA PLATFORMS, Q4 2022.
MongoDB-Forrester.png.webp
Since the time I began to follow Saul’s advice and the contributions from everyone here:
| 2018 | +38.9% |
|---|---|
| 2019 | +32.9% |
| 2020 | +203% |
| 2021 | +46.8% |
| 2022 | MTD | YTD |
|---|---|---|
| January | (-)22.3% | (-)22.3% |
| February | 6.4% | (-)17.3% |
| March | (-)1.77%. | (-)18.8% |
| April | (-)21.76% | (-)36.5% |
| May | (-)25.8%. | (-)52.9% |
| June | 8.17%. | (-)49% |
| July | 1.51% | (-)48.3% |
| Aug | 12% | (-)42% |
| Sept | (-)13.9%. | (-)50% |
| Oct | (-)3.8% | (-)52% |
| Nov | (-)13.13% | (-)58.3% |
| Dec | (-)0.007% | (-)58.55% |
(-)58.55% is 3.67% more than what I’d have in returns if I’d simply kept all the shares owned in each position from the beginning of the year. This may appear to be very little to show for a years effort. Of course, It’s the increase in confidence my investing decisions afford and my enjoyment of the process that matter.
12/6/22
What I did: Before the end of SentinelOne’s Conference Call, I sold nearly all of my 11% Crowdstrike position and bought SentinelOne with the money.
Why I did It: I had maintained that I was only going to buy the Leader in this Market and Crowdstrike is the Leader. I reasoned that there should be some advantages to being the leader. My attempt to maintain this reasoning was overcome by SentinelOne’s tremendous Revenue Growth rate and incredible margin expansion, over this last year.
From the CC-
SentinelOne repeatedly expressed the strength in there pipeline and conservative nature of their guides in Q4. So even with a much more conservative guide they are planning to significantly outperform Crowdstrike in both top line growth and margin expansion (I am clear here, in that Crowdstrike is up against the ‘law of large numbers’.). In their CC, we have Crowdstrike having said that they’re moving into the SMB market and now complaining about it. And we have SentinelOne having said that they were going to move into the larger Enterprises and then doing it above my expectations.
12/12/22
What I did: I sold about 1/2 the 9% position I just acquired SentinelOne in order to buy back Datadog at $77/share.
Why I did it: With Sentinel One being the newest onto my portfolio, I decided that I’m more comfortable with 5% than 9% and…
I’d posted on my assumptions about the Security portion of my portfolio, in general. This got me thinking about being seat based verses consumption based business models and I decided I wanted to be More in the consumption based (Datadog) when usage inevitably ticks back up. This is not as much a macro play as it sounds. My understanding is that the ramp in Fedral spending for Security will be perhaps as slow as the return to a risk on investment environment, playing out over the next couple years. Put to Call ratios are 1.5. I’m just saying that the Fear index is crazy high. I’m feeling a bottom.
12/19/22
What I did: I sold the remaining 5% position in SentinelOne, a little bit of my 2% position Zscaler and a tiny bit of Datadog to bring Crowdstrike back to a 5% position and brought my Bill position up about 15%.
Why I did it: I’d said I’d be adding back to CRWD opportunistically. Sentinel was upm17% from when I bought a week ago and Crowdstrike is down again.
Bert re Crowdstrike: DFCF valuation is 93% greater than the current share price, using the company’s free cash flow projection for its FY ’24 year, with fairly consistent growth thereafter and a 8.5% weighted average cost of capital which is based on the Finbox metric. While that 93% appreciation potential may seem hard to believe at this point, it really shows how divergent valuations have become from valuations based on growth and growth of free cash flow.
No longer valuing DFCF, IMHO, is just be the strongest indicator of Max Fear in the market I’ve seen. When even Crowdstrike is taken down to this level, there is only up from here, IMO.
What I learned this month, increasing my confidence in Snowflake.
Snowpipe Streaming
Snowpipe is their ingest system for batch importing files from a data lake, which takes about 60s on average to appear in Snowflake. The new Snowpipe Streaming greatly improves that, so that streaming data is now visible in 1-2s. They currently allow a GB/second ingest into a table, and stated it will go public preview soon. Dynamic Tables are their new mechanism to blend streaming data with existing data tables. Under the hood it handles it as a materialized view, to auto-increment the entire query as needed as new data streams in.
What I learned recently, increasing my confidence in cloudflare.
Birthday Week at the end of October, Cloudflare pointed out how further development of their existing technology is expected to coalesce.
Queues when combined with an increase to the size limit, could create an API-driven global data streaming & event messaging platform like Confluent Kafka, Azure Event Hubs, AWS Kinesis, Redpanda, Ably, or Macrometa (a db partner in Workers).
• If Cloudflare moves into data streaming, you can easily see them taking the extra step to have inline stream processing capabilities by running Workers alongside Queues, such as Confluent Kafka Streams and AWS Kinesis + Lambda.
And if Cloudflare doesn’t create abstraction layers over data streaming & stream processing, I imagine new edge-native startups might be created in Workers to do just that
And…in Q3 Cloudflare made this available…
Cloudflare-CustomerActivity.png.webp
Peter Offringa-
In addition to the large customer ($100K in annualized revenue) metric, Cloudflare leadership periodically shares counts of customers exceeding the $500K and $1M spend levels. Customers spending more than $500K were up 88% year/year, compared to 58% when the metric was last shared in Q1. Customers spending more than $1M were up 63% y/y in Q3, as compared to 72% in Q1. Cloudflare also reached 75 customers spending more than $1M in Q3. Management pointed out that these growth rates in high spending customers were higher than the growth rate of revenue.
As further evidence of large customer penetration, management shared that 32% of the Fortune 500 are currently customers of Cloudflare. The CEO thinks this could grow to 100% as they continue improving their enterprise sales motion and adding more products to the portfolio. Once landed, customers of this size provide a lot of room for spend expansion.
What I learned recently, increasing my confidence in Datadog.
From what was released at Dash, Muji
Datadog Workflows was introduced as a new no-code/low-code tool for building automated workflow pipelines. This is akin to the types of workflow automation you can do in Monday.com and Asana do for business operations, but is highly honed for DevOps and security use cases. This is not that surprising of an addition, as every SIEM needs a SOAR to take action – but it goes way beyond a SOAR, as they also allow for handling DevOps use cases around app and app stack deployment. This is a whole new tool to handle use cases and automated tasks around the DevOps workflow and CI/CD pipeline, and I expect it to be an incredibly popular addition to their platform. There are 600+ actionsalready supported across AWS, Cloudflare, Fastly, GitHub, Jira, Slack, Okta, PagerDuty, and ServiceNow. This is public beta for now, and it isn’t clear if it will be a priced product, but I am guessing it might become a core addition to the platform that improves the stickiness