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: 7132
Venue: SIGMOD
Year: 2025
Pagerank: 4.1945683e-05
Overall Rank: 10,425 | 27.48%
DOI: 10.1145/3722212.3725083

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Rank	Citing Paper	Year	Venue	Pagerank

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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
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036721403
359	Self-Driving Database Management Systems	2017	CIDR	0.0002592783
884	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.00015654004
2,047	Automatically Indexing Millions of Databases in Microsoft Azure SQL Database	2019	SIGMOD	9.6920209e-05
4,240	Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation	2021	VLDB	6.3318228e-05
4,590	MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems	2021	SIGMOD	6.0620053e-05
6,379	A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning	2023	SIGMOD	5.0909479e-05
8,020	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	4.6040862e-05
9,006	Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems	2024	VLDB	4.4101482e-05
9,467	Database Gyms	2023	CIDR	4.3346412e-05

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