It's trivially easy to beat Snowflake on
latency because its latency is truly awful. It often takes 1-4 SECONDS end-to-end to run a query that touches just a few thousand (not million!) rows. In theory this is fine for OLAP but when you have a Looker dashboard with 20+ tiles, it becomes a serious problem. ClickHouse absolutely thrashes Snowflake at this, routinely running millions-of-rows queries in hundreds of milliseconds.
Anyway the specific thing I'm remembering about cost is a case where a data team I joined had built a (dumb) CI process that ran a whole DBT pipeline when a PR was opened. After a month or so we got a bill for something like $50k.
Snowflake's rack-rate pricing is $2/credit and an XS warehouse is 1 credit/hr. That XS warehouse is, allegedly, an 8-core/16GB(?) instance with about a hundred gigs of SSD cache, from a "c" family if you're on AWS. Of course since your data is in S3 (cache notwithstanding), you're likely to be network-constrained for many query patterns. BigQuery, which is unquestionably faster than Snowflake, proves that this can be done efficiently. But compare to Redshift (non-RA3) or ClickHouse where you have data in locally-attached disks, Snowflake just gets smoked. The only lever they give you to get more performance is to spend more money which is great for their bottom line but bad for you.
The pitch is that because you can turn it all off when you're not using it (which in fairness they make very easy!), the overall costs end up low. Ehhhhhhhhhhh, maybe. It only takes one person leaving a Looker dashboard open with auto-refresh enabled to keep a warehouse constantly online, and that will add up fast. Plus if you are being silly and building DW data hourly, as is popular, it's going to need to be on anyway. (Do daily builds! You don't need more than that!) Point being, the cost model you will get from sales reps makes very optimistic assumptions about utilization, and it is very likely you will be hit with a bill larger than expected. In practice while it is technically easy to control utilization, it is not actually easy because there are humans in the loop.