At the extreme end of this, you could also append a new row for every event and count them. If the number of rows would be too big over some period of time, you could similarly aggregate them occasionally and clear the "scratch" table.
One side benefit of this approach is that getting the final aggregate is cheap, where compacting an append-only log table might not be.
This makes some intuitive sense, though: general purpose databases are expected to be _pretty good_ at handling the case of "add new data" with no other specific conditions, e.g. on other rows or tables' existing data.
I also agree with your last point. Running count() all day on this wouldn't be great, and compaction would take real time. I assumed that most high throughput write scenarios for something like an event count or view count can be a few minutes (or hours, or days) out of date, at which point read caching would be my first stop before clever summation algorithms, which are still pretty cool.