Cassandra Practice Test

Apache Cassandra utilizes a wide-column store data model, which is designed to handle large volumes of data across distributed systems. This model allows data to be stored in a table structure similar to a relational database, but with some important differences. In Cassandra, rows are identified by a unique key, and each row can have a different number of columns, which provides flexibility in how data is organized.

The wide-column store model is particularly advantageous for applications that require quick access to large datasets, as it supports high write and read throughput. It allows for efficient querying of data, thanks to its use of partitioning and clustering keys that determine how data is distributed across the nodes in the Cassandra cluster.

This approach enables Cassandra to scale horizontally by adding more nodes to the cluster, effectively managing increasing amounts of data without compromising performance. It also allows for powerful querying capabilities, such as retrieving data based on specific column values, which is a hallmark of wide-column databases.

In contrast, other data models like key-value stores provide a more simplistic approach, focusing on simple key-based retrieval without the advanced querying capabilities found in a wide-column structure. Document stores are centered around documents saved in formats like JSON, which are less flexible than the wide-column concept of having different columns for each row