Apache Cassandra provides an easy way to scale data across multiple nodes and datacenters with fault tolerance and data redundancy. However, in practice, Cassandra has proven to be expensive and problematic due to several key limitations of the underlying architecture.
This paper explores four core issues at the root of common problems encountered running Cassandra in production. Read it to explore:
- The root causes of Cassandra’s administrative burden, inconsistent and high latencies, timeouts, node sprawl, and other common issues
- Where Cassandra’s underlying architecture forces tradeoffs
- Ways to address these shortcomings without changing your application