USENIX ATC2020顶会
SplinterDB: Closing the Bandwidth Gap for NVMe Key-Value Stores
Alexander Conway, Abhishek Gupta, Vijay Chidambaram, Martin Farach-Colton, Richard P. Spillane, Amy Tai, Rob Johnson
摘要
Modern NVMe solid state drives offer significantly higher bandwidth and lower latency than prior storage devices. Current key-value stores struggle to fully utilize the bandwidth of such devices. This paper presents SplinterDB, a new keyvalue store explicitly designed for NVMe solid-state-drives.
SplinterDB is designed around a novel data structure (the STB ε -tree) that exposes I/O and CPU concurrency and reduces write amplification without sacrificing query performance. STB ε -tree combines ideas from log-structured merge trees and B ε -trees to reduce write amplification and CPU costs of compaction. The SplinterDB memtable and cache are designed to be highly concurrent and to reduce cache misses.
We evaluate SplinterDB on a number of micro-and macro-benchmarks, and show that SplinterDB outperforms RocksDB, a state-of-the-art key-value store, by a factor of 6-10× on insertions and 2-2.6× on point queries, while matching RocksDB on small range queries. Furthermore, SplinterDB reduces write amplification by 2× compared to RocksDB.
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引用它的顶会 Paper35
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- Differentiated Key-Value Storage Management for Balanced I/O PerformanceYongkun Li, Zhen Liu, Patrick P. C. Lee, Jiayu Wu 等USENIX ATC 2021 · 被引用 79 次
- ChameleonDB: a key-value store for optane persistent memoryWenhui Zhang, Xingsheng Zhao, Song Jiang, Hong JiangEuroSys 2021 · 被引用 72 次
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