Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging
Summary: Dostoevsky uses Lazy Leveling to remove merges from all LSM-tree levels except the largest, lowering update I/O while preserving lookup and storage bounds. It generalizes to Fluid LSM-tree for adaptive, workload-hardware aware merging; implemented atop RocksDB, it empirically dominates state-of-the-art in performance and space. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Niv Dayan (Harvard University)
- 2. Stratos Idreos (Harvard University)
BibTeX Citation
@inproceedings{dayan_sigmod18,
title = {{Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging}},
author = {Dayan, Niv and Idreos, Stratos},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196927},
url = {https://dl.acm.org/doi/10.1145/3183713.3196927},
year = {2018}
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