One of the challenges faced by distributed systems is how to keep the replicas consistent with each other. Maintaining consistency requires balancing availability and partitioning. Fortunately, Apache Cassandra lets us tune this balancing according to our needs. In this blog, we are going to see how we can tune consistency levels during reads and writes to achieve faster reads and writes.
Before digging more about consistency, let me first discuss CAP Theorem. CAP Theorem describes the tradeoffs in distributed systems; it states that any networked shared-data system can have at most two of three desirable properties: