Back to papers
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
- 7476
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 5.1725247e-05
- Overall Rank
- 10,164 | 29.36%
- DOI
-
10.1145/3786649
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
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 |
| 89 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00035598024 |
| 223 |
OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases |
2014 |
VLDB |
0.000243333 |
| 334 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00020961385 |
| 493 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00017600244 |
| 1,324 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.0001126122 |
| 1,335 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00011217342 |
| 2,428 |
GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization |
2024 |
VLDB |
8.6581081e-05 |
| 2,859 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
8.094221e-05 |
| 3,161 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
7.7501079e-05 |
| 3,168 |
iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases |
2019 |
VLDB |
7.7448853e-05 |
| 3,298 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
7.6094798e-05 |
| 3,430 |
CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions |
2021 |
VLDB |
7.4959348e-05 |
| 3,539 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.3903311e-05 |
| 3,963 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
7.0613767e-05 |
| 4,734 |
iTuned: A Tool for Configuring and Visualizing Database Parameters |
2010 |
SIGMOD |
6.6019694e-05 |
| 5,095 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
6.4313378e-05 |
| 5,283 |
Machine Learning for Databases |
2021 |
VLDB |
6.3568612e-05 |
| 7,261 |
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model |
2025 |
VLDB |
5.715327e-05 |
Semantically Similar Papers