I'm curious how QuestDB handles dimensions. OLAP support with reasonably large number of dimensions and cardinality in the range of at least thousands is a must for modern-day time series database. Otherwise, what we get is only incremental improvement to Graphite -- a darling among startups, I understand, but a non-scalable extremely hard to use timeseries database nonetheless.

A common flaw I see in many time-series DBs is that they store one time series per combination of dimensions. As a result, any aggregation will result in scanning of potentially millions of time series. If any time-series DB claims that it is backed up by a key-value store, say, Cassandra, then the DB will have the aforementioned issue. For instance, Uber's M3 used to be backed up by Cassandra, and therefore would give this mysterious warning that an aggregation function exceeded the quota of 10,000 time series, even though from user's point of view the function dealt with a single time series with a number of dimensions.