SplinterDB: Closing the Bandwidth Gap for NVMe Key-Value Stores

Abstract

Modern NVMe solid state drives offer significantly higher bandwidth and low latency than prior storage devices. Current key-value stores struggle to fully utilize the bandwidth of such devices. This paper presents SplinterDB, a new key-value store explicitly designed for NVMe solid-state-drives. SplinterDB is designed around a novel data structure (STB^ε-tree), a co-designed memtable, and a concurrent replacement for the page cache. STB^ε-trees combine ideas from log-structured merge trees and B^ε-trees to reduce write amplification and CPU costs of compaction. The 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 6–10x on insertions and 2–2.6x on point queries, while matching RocksDB on small range queries. Furthermore, SplinterDB reduces write amplification by 2x compared to RocksDB.