Cassandra Practice Test 2026 – Comprehensive All-in-One Guide to Exam Success!

The characteristic that is crucial for the scalability of Cassandra is horizontal scalability. This design allows Cassandra to increase its capacity and handle more workload simply by adding more nodes to the cluster without any significant downtime or reconfiguration. Horizontal scalability is achieved through a distributed architecture where all nodes are equal, and data is automatically partitioned across them.

This means that as the system grows, additional nodes can be added to distribute the data and the load evenly, enhancing performance and storage capacity seamlessly. In contrast to centralized systems, which can become bottlenecked as they scale, Cassandra's ability to function efficiently with many nodes allows it to maintain performance levels even as demands increase.

Other options, such as centralized design and limited node addition, inherently restrict scalability, as they do not facilitate straightforward expansion. Extensive use of caching, while it can improve performance, is not a defining factor for scalability itself. Thus, horizontal scalability is the key characteristic that enables Cassandra to effectively grow and manage large volumes of data.