Reads definitely aren't cheap, not compared to the hyper-optimized write path. Cassandra reads can however be exploited to make a lot of common time-series reads extremely cheap by amortizing the cost of the read over a lot of returned data (think a clustered row with lots of byte-sorted columns). Not that RDBMSes can't do the same thing, but it's a complex challenge to linearly scale and maintain availability.
Cassandra also exploits SSDs quite well by avoiding write-amplification problems, given that all write IO is sequential only.
I'm a huge fan of both traditional RDBMSes and alternative data stores. The most important rule for touring data stores is to be sure not to bring it into work when it's not appropriate and to evaluate the hell out of any solution before you write a single line of code.
Most of the time, PostgreSQL will do 99.9% of what you need and then some.
Cassandra also exploits SSDs quite well by avoiding write-amplification problems, given that all write IO is sequential only.
I'm a huge fan of both traditional RDBMSes and alternative data stores. The most important rule for touring data stores is to be sure not to bring it into work when it's not appropriate and to evaluate the hell out of any solution before you write a single line of code.
Most of the time, PostgreSQL will do 99.9% of what you need and then some.