Optimizing performance in ScyllaDB deployments involves selecting the appropriate compaction strategy, a critical decision impacting application efficiency. Compaction, a process of merging sstables to reduce disk space usage and improve read performance, poses challenges due to its resource-intensive nature, affecting CPU, memory, and disk I/O. The default Size-Tiered Compaction is effective for write-intensive tasks but can leave large sstables lingering, while Leveled Compaction is suited for read-heavy workloads by maintaining smaller, fixed-size sstables, albeit with increased I/O on writes. To address workloads requiring both read and write efficiency, ScyllaDB introduced Hybrid Compaction in ScyllaDB Enterprise, combining the strengths of both strategies to enhance disk space management without compromising system performance. Additional strategies exist, but these core options offer tailored solutions depending on specific workload demands, as explored in the ScyllaDB Summit 2017.