Cassandra is a great tool for solving specific problems, but it is not a general-purpose data store. Considering the prior section where we discussed the read and write paths, there are some obvious scenarios in which Cassandra is not the correct choice of the data store. These are important to remember, and we will discuss them in this section:
Cassandra reconciles data returned from both memory, disk, and read-time.
Primary keys in Cassandra are unique. Therefore there is no difference between an insert and an update in Cassandra; they are both treated as a write operation. Given that its underlying data files are immutable, it is possible that multiple writes for the same key will store different data in multiple files. The overwritten data doesn't automatically go away. It becomes obsolete (due to its timestamp).
When Cassandra processes a read request, it checks for the requested data from both memory and disk. If the requested data was written...
