Designing for immutability
An interesting and important difference between modeling relationships versus modeling time-series data is that relational data tends to be mutable whereas time-series data is generally immutable. Mutable data is unstable because it may change at any moment. This makes it more complicated to guarantee we have the most up-to-date version. Immutable data, by contrast, is stable, which means we can avoid many of the complexities associated with data that can change over time.
Tip
If you find yourself struggling with modeling a particular problem in Cassandra, consider reimagining the model as immutable time-series data. This strategy often results in an obvious solution to what appeared to be an intractable problem.
Immutability is a desirable property in a Cassandra data model as updates and deletes can add complexity related to consistency and performance (remember that SSTables are immutable). Often the easiest way to guarantee immutability is to simply add a time...
