In this chapter, we introduced the Cassandra database, and discussed its features and acceptable use cases, as well as providing some example code for working with it. Cassandra has some intrinsic features that certainly make it a desirable backend data store. It can serve data in an environment with no single point of failure, as well as provide tunable consistency, linear scalability, and best-in-class data center awareness.
Common use cases for Cassandra include time series or event-driven data. It has also shown its ability to support large datasets, which continue to grow over time. Applications backed by Cassandra are successful when they use tables designed to fit well-defined, static query patterns.
It is important to remember that Cassandra also has its share of anti-patterns. Cassandra typically does not perform well with use cases architected around frequently updating or deleting data, queue-like functionality, or access patterns requiring query flexibility. Improper setup...
