SpacKV: A Pmem-Aware Key-Value Separation Store Based on LSM-Tree

Abstract

Key-value (KV) stores based on persistent memories such as Intel Optane Pmem can deliver higher throughput and lower latency, compared to traditional SSD/HDD. Many KV stores adopt LSM-tree as the bone index structure. However, LSM-tree suffers from severe write amplification, which degrades the system’s performance and exacerbates the wearout of persistent memory. In this paper, we propose SpacKV, a hybrid DRAM-Pmem KV store, which applies a KV separation scheme and exploits Pmem’s device characteristics to achieve high throughput. We design a dedicated value storage structure to maintain localized order of values for efficient range queries and a compaction-triggered garbage collection mechanism to minimize intermediate I/O overhead. Moreover, we leverage Pmem’s key features: byte-addressability, access unit of 256 bytes and specific persistence instructions to further mitigate the write amplification effect. The experimental results show that SpacKV achieves 1.4–10.8$\times$, 4.7–9.7$\times$, and 6.7–13.5$\times$ in terms of write, read, and range query performance over three state-of-the-art LSM-tree based KV stores: LevelDB-Pmem, RocksDB-Pmem, and MatrixKV, respectively.

X. Ge and M. Lai—These authors contributed equally to this work.