Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym

Summary: DB-Gym: extensible, open-source framework with a standardized API to compose autonomous DBMS tuning, ML models, workload capture, and evaluation. Demonstrates head-to-head human versus automated tuner under stress to benchmark ML-driven optimization. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 7194
Venue: SIGMOD
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 10,706 | 26.55%
DOI: 10.1145/3722212.3725083

Incoming Non-self Citations Over Time

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Authors

1. Patrick Wang (Carnegie Mellon University)
2. Wan Shen Lim (Carnegie Mellon University)
3. William Zhang (Carnegie Mellon University)
4. Samuel Arch (Carnegie Mellon University)
5. Andrew Pavlo (Carnegie Mellon University)

BibTeX Citation

@inproceedings{wang_sigmod25,
        title = {{Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym}},
        author = {Wang, Patrick and Lim, Wan Shen and Zhang, William and Arch, Samuel and Pavlo, Andrew},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3722212.3725083},
        url = {https://dl.acm.org/doi/10.1145/3722212.3725083},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
86	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00035316107
234	Self-Driving Database Management Systems	2017	CIDR	0.00023810722
563	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.0001650812
1,548	Automatically Indexing Millions of Databases in Microsoft Azure SQL Database	2019	SIGMOD	0.00010392475
3,586	Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation	2021	VLDB	7.2834069e-05
3,961	MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems	2021	SIGMOD	6.987575e-05
6,600	A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning	2023	SIGMOD	5.8250114e-05
7,846	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	5.5331459e-05
8,984	Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems	2024	VLDB	5.3395569e-05
9,536	Database Gyms	2023	CIDR	5.2529727e-05

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