A key-value store for modern storage devices


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 key-value store explicitly designed for NVMe solid-state-drives.

SplinterDB is designed around a novel data structure (the STBε-tree) that exposes I/O and CPU concurrency and reduces write amplification without sacrificing query performance. STBε-tree combines ideas from log-structured merge trees and Bε-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.

On a number of micro- and macro-benchmarks, 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.

Learn more about SplinterDB on VMware's Open Source Blog: Introducing SplinterDB: A High-Performance Key-Value Store


SplinterDB is open source. The code is available on github:


  • Our USENIX ATC 2020 paper introduces size-tiered Bε-trees and SplinterDB, a key-value store that outperforms RocksDB by up to an order of magnitude.


SplinterDB is being incubated as part of VMware's tech transfer programs.

SplinterDB Incubation Leader: Carlos Garcia-Alvarado (VMware)

SplinterDB Incubation Team: Aditya Gurajada, Eric Hoffman, Gabriel Rosenhouse


2022 Interns

2021 Interns

External Researchers

  • Martin Farach-Colton

Related Publications


  • Active VMW Software Systems Projects

Research Areas

  • Data Structures
  • Databases
  • External-Memory Data Structures
  • Key-Value Stores
  • Write-Optimized Data Structures