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Optimizing Space Amplification in RocksDB

Summary: Introduces practical techniques to minimize space amplification in RocksDB—trading CPU and read/write amplification via compaction/tuning—to prioritize storage efficiency while preserving OLTP latency targets. Empirical (TPC-C, LinkBench, production) results show RocksDB uses <50% of InnoDB storage and often matches or exceeds its performance, demonstrating the first large-scale competitive LSM deployment for OLTP. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
308
Venue
CIDR
Year
2017
Pagerank
0.000179044
Overall Rank
472 | 96.77%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{dong_cidr17,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '17},
        title = {{Optimizing Space Amplification in RocksDB}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Dong, Siying and Callaghan, Mark and Galanis, Leonidas and Borthakur, Dhruba and Savor, Tony and Stumm, Michael},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 51 citing papers.

Rank Citing Paper Year Venue Pagerank
11,372 Optimal Uncoordinated Unique IDs 2023 PODS 5.093636e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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