Not every workload fits the same storage shape. While LSM trees optimize for write throughput and range scans, frequently overwritten data and KV workloads require significant compaction I/O to minimize read amplification in a timely fashion. This talk explores how ScyllaDB built a new storage engine to eliminate LSM traversal entirely, enabling a single deployment to handle both wide-column and key-value workloads without compromise. We’ll cover the motivations behind the design, the tradeoffs it explicitly inherits, and early performance results.
