ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning

Summary: ESTune accelerates database knob tuning by early-stopping clearly poor configurations, replacing full-workload evaluation with high-confidence performance estimates from partial runs. Core novelty: a hybrid Bayesian NN plus MAML few-shot/meta-learning to predict configuration performance uncertainty and preserve tuning quality. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID: h00dce62817921b37
Venue: SIGMOD
Year: 2026
Pagerank: 4.9793485e-05
Overall Rank: 10,641 | 28.46%
DOI: 10.1145/3786649

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Zhongwei Yue (Henan Normal University)
2. Jun-Peng Zhu (East China Normal University)
3. Peng Cai (East China Normal University)
4. Xuan Zhou (East China Normal University)
5. Quanqing Xu (Ant Financial)
6. Chuanhui Yang (Ant Financial)

BibTeX Citation

@inproceedings{yue_sigmod26,
        title = {{ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning}},
        author = {Yue, Zhongwei and Zhu, Jun-Peng and Cai, Peng and Zhou, Xuan and Xu, Quanqing and Yang, Chuanhui},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3786649},
        url = {https://dl.acm.org/doi/10.1145/3786649},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
78	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036684414
235	OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases	2014	VLDB	0.00023697028
314	An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning	2019	SIGMOD	0.00021282642
437	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB	0.00018315867
1,250	DB-BERT: A Database Tuning Tool that "Reads the Manual"	2022	SIGMOD	0.00011339256
1,289	An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems	2021	VLDB	0.00011162479
2,231	GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization	2024	VLDB	8.7982985e-05
2,720	ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases	2021	SIGMOD	8.0966919e-05
2,772	Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation	2022	VLDB	8.035288e-05
3,032	iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases	2019	VLDB	7.7351139e-05
3,051	LlamaTune: Sample-Efficient DBMS Configuration Tuning	2022	VLDB	7.7055931e-05
3,158	CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions	2021	VLDB	7.5811757e-05
3,486	HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements	2022	SIGMOD	7.2636102e-05
4,079	Towards Dynamic and Safe Configuration Tuning for Cloud Databases	2022	SIGMOD	6.818264e-05
4,741	Machine Learning for Databases	2021	VLDB	6.4410027e-05
4,862	iTuned: A Tool for Configuring and Visualizing Database Parameters	2010	SIGMOD	6.3786959e-05
5,286	An Efficient Transfer Learning Based Configuration Adviser for Database Tuning	2024	VLDB	6.1971399e-05
7,070	E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model	2025	VLDB	5.6080535e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	11,287	AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines	2025	VLDB
2	437	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB
3	314	An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning	2019	SIGMOD
4	10,580	MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration	2026	SIGMOD
5	9,620	Db2une: Tuning Under Pressure via Deep Learning	2024	VLDB
6	9,904	AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning	2026	SIGMOD
7	78	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD
8	2,231	GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization	2024	VLDB
9	4,079	Towards Dynamic and Safe Configuration Tuning for Cloud Databases	2022	SIGMOD
10	7,070	E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model	2025	VLDB