What effect do compaction strategies have on performance in Cassandra?

Compaction strategies play a crucial role in how data is managed and stored in Cassandra, directly influencing both read and write performance as well as how efficiently disk space is utilized.

When data is written to Cassandra, it is initially placed in memory tables before being flushed to disk. Over time, multiple SSTables (sorted string tables) are created on disk. Compaction strategies determine how these SSTables are merged and reorganized, which affects the efficiency with which data can be read or written. For example, a well-chosen compaction strategy can minimize write amplification and reduce the number of SSTables that need to be read when executing a query, thereby improving read performance.

Additionally, different compaction strategies have different implications for disk space usage. Some strategies, like TimeWindowCompactionStrategy, can efficiently manage time-series data, ensuring older data is compacted and removed based on retention policies, which helps maintain optimal disk usage.

In summary, the correct choice highlights the significant impact of compaction strategies on overall system performance, particularly concerning the efficiency of read and write operations and the management of disk space.