I too believe it is the best fit, but the "aggregate functions" gets most people. The use of counter columns is very limiting and many engineers don't want to struggle with storing state during streaming writes to precalculate the aggregates on write. Also, engineers tend not to want to do large reads to rebuild large aggregate values on small data changes.

It is what we use, and we use spark streaming for the rollups. We had evaluated Influx, OpenTSDB, and Druid also. So long as you know the exact read patterns for your client I think Cassandra is definitely the best fit for most things.