It depends on the business unit. Some don't have the ability to run a technology group to run a $10K dedicated server.

I don't think it's always that easy. I work on some large databases (1TB+) where even queries utilizing indexed columns still take prohibitively long to run. Sure we could look into partitioning (and we likely might) but then more work is progressively falling on engineering to keep the system running for the standards of analysts but not necessarily the product.

BigQuery in these cases has been very useful. Everything I throw at it returns in seconds. I can also do more text comparison queries that on a standard RDBMS would have required a full text index (which would probably be huge). But with BigQuery even those queries take seconds and I don't have to take production resources to view it.

The example in the article is 40k/day for querying on 14 GB of data, every second. You can do that on a ~100/month machine or a somewhat modern laptop.

Importantly it depends on how often these things are run and who has to maintain a server.