Often the best comments start off exactly like yours: it's clear you feel very strongly about the issue, so edit it and say how/why!! list the points that irked you.
One I worked at used a framework designed for SQL, wrote a Cassandra storage backend, didn't denormalize data at all (!) and then (badly) performed JOINs in software because the framework was built around the storage having relational operations (!!) topped off by their backend implementation not being aware of partitioning keys, and hence using unique values for them (!!!).
The first two I discovered when trying to diagnose why certain parts of our website/API were extremely slow. The third I discovered mid-import when suddenly the (staging) cluster stopped being able to process queries.
There wasn't any problem Cassandra was solving, our read volume was much higher than our write volume (like, 10x-100x), and we didn't even have that much data in the first place. Premature optimization (for a problem we were a long way from having) and being trendy.
I don't think Cassandra is particularly bad (and can be used in awesome ways for high-write, low-read immutable timeseries data) but you have to use Cassandra as Cassandra, not as a trendy MySQL.