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A Top-Down Approach to Achieving Performance Predictability in Database Systems
Summary: Top-down study of performance predictability across MySQL, PostgreSQL, and VoltDB using TProfiler identifies key latency-variance sources. Proposes Variance-Aware Transaction Scheduling (VATS) and a lazy buffer-pool policy, yielding up to 5.6x variance reduction and 6.3x 99th percentile latency, with VATS adopted in MySQL/MariaDB.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h75664b9b9ce75554
Venue
SIGMOD
Year
2017
Pagerank
6.3369302e-05
Overall Rank
4,932 | 66.95%
DOI
10.1145/3035918.3064016
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{huang_sigmod17,
title = {{A Top-Down Approach to Achieving Performance Predictability in Database Systems}},
author = {Huang, Jiamin and Mozafari, Barzan and Schoenebeck, Grant and Wenisch, Thomas F.},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3064016},
url = {https://dl.acm.org/doi/10.1145/3035918.3064016},
year = {2017}
}
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SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service 2013
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