Basic Rules of Cassandra Data Modeling

Designing an efficient data model for Apache Cassandra requires understanding its basic rules and goals. The main objectives are to spread data evenly across nodes and minimize the number of partitions read during queries. Developers coming from a relational background should avoid applying traditional modeling rules to Cassandra, as it is optimized for high write throughput and denormalization. To achieve efficient reads, model your data around specific query patterns rather than relations or objects. Use compound partition keys to balance the two goals when necessary. Consider using time ranges for splitting partitions based on query patterns, and remember that data duplication is acceptable in Cassandra.