Leveraging NVMe SSDs for Building a Fast, Cost-effective, LSM-tree-based KV Store

AbstractKey-value (KV) stores support many crucial applications and services. They perform fast in-memory processing but are still often limited by I/O performance. The recent emergence of high-speed commodity non-volatile memory express solid-state drives (NVMe SSDs) has propelled new KV system designs that take advantage of their ultra-low latency and high bandwidth. Meanwhile, to switch to entirely new data layouts and scale up entire databases to high-end SSDs requires considerable investment. As a compromise, we propose SpanDB, an LSM-tree-based KV store that adapts the popular RocksDB system to utilize selective deployment of high-speed SSDs. SpanDB allows users to host the bulk of their data on cheaper and larger SSDs (and even hard disc drives with certain workloads), while relocating write-ahead logs (WAL) and the top levels of the LSM-tree to a much smaller and faster NVMe SSD. To better utilize this fast disk, SpanDB provides high-speed, parallel WAL writes via SPDK, and enables asynchronous request processing to mitigate inter-thread synchronization overhead and work efficiently with polling-based I/O. To ease the live data migration between fast and slow disks, we introduce TopFS, a stripped-down file system providing familiar file interface wrappers on top of SPDK I/O. Our evaluation shows that SpanDB simultaneously improves RocksDB's throughput by up to 8.8\(\) and reduces its latency by 9.5–58.3%. Compared with KVell, a system designed for high-end SSDs, SpanDB achieves 96–140% of its throughput, with a 2.3–21.6\(\) lower latency, at a cheaper storage configuration.