Yep. The nature of the time series data does allow for storage optimizations like that. But there is the usage pattern aspect as well, that is more interesting in my opinion.

- Availability preferred over consistency (you want your metrics when bad things are happening, even if they may not be 100% accurate)

- Extremely write heavy, with most data never being read (they mentioned that only 2% of data is ever read. in my experience at another large company, it was way less than 2%)

- For the data that is read, most of reads are for most recent points (mostly alarms, but some dashboards as well)

- Different SLAs for queries based on usage - ie. queries for alarms must be fast. Dashboards, and trend analysis - not so much.