Fair point, some of that net revenue increase is because of consolidation of workloads, although the majority of the cost is likely still driven by consumers expanding usage beyond what they expected. As I mention in my article, the second part of increase in costs has to do with data governance, and my argument is that snowflake doesn't make governance easy. Why can't they stand up a IAM-like service with a nice UI and dashboards? why can't they make integrations with pagerduty, slack, email work out of the box? Why can't I specify team based budgets and instead have to do it on a per warehouse-team basis? Why do I have to build custom bespoke tooling on top to make governance work?
I can unequivocally say that at a certain scale you need to move on and that Snowflake and many of the SaaS providers are too expensive even at medium scale companies. This article describes this paradox better than I could: https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap...
Moreover Snowflake's enterprise pricing model is even more non-scalable. Why do companies often have to pay two times higher price per credit relative to the standard model? Shouldn't guarantees on security or support come with a fixed cost? Shouldn't enterprise offer economies of scale in pricing?
I also wish folks would read my article from end to end because my conclusion in the article is that you don't really have a choice but to use an enterprise solution when your scale is small. If I had to start my own company and had only 2 data engineers, you betcha I would use Snowflake and DataBricks.
--- btw, it really surprises me that nobody has commented on the workload manager. Am I the only one seeing that as an issue? I have enough exposure to compare it with Redshift and I can say that Snowflake's workload manager is just very bad at optimizing throughput.