DBScholar

Back to papers

Towards Dynamic and Safe Configuration Tuning for Cloud Databases

Summary: OnlineTune tunes online cloud DBs under dynamic workloads with contextual BO and context-space partition. Safety via black-box/white-box checks and subspace adaptation; results show large gains and far fewer unsafe configurations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc2416b9e60373b8e
Venue
SIGMOD
Year
2022
Pagerank
6.7930727e-05
Overall Rank
4,101 | 72.52%
DOI
10.1145/3514221.3526176

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod22,
        title = {{Towards Dynamic and Safe Configuration Tuning for Cloud Databases}},
        author = {Zhang, Xinyi and Wu, Hong and Li, Yang and Tan, Jian and Li, Feifei and Cui, Bin},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526176},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526176},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 23 of 23 citing papers.

Rank Citing Paper Year Venue Pagerank
2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.7924681e-05
2,779 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.0085666e-05
5,098 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 6.2631174e-05
5,304 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 6.1758143e-05
6,464 Towards General and Efficient Online Tuning for Spark 2023 VLDB 5.759941e-05
6,752 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6733557e-05
7,092 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.5868637e-05
8,026 A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning 2024 VLDB 5.3884724e-05
9,041 Optimizing the cloud? Don't train models. Build oracles! 2024 CIDR 5.2183053e-05
9,052 Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment 2025 SIGMOD 5.215088e-05
9,946 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.0910746e-05
9,995 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.0845476e-05
10,123 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 5.0638787e-05
10,324 Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents 2026 VLDB 5.0241309e-05
10,366 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 5.0091669e-05
10,653 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.9605343e-05
10,713 ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning 2026 SIGMOD 4.9605343e-05
10,957 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9605343e-05
11,142 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9605343e-05
11,173 Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions 2025 SIGMOD 4.9605343e-05
11,273 High-Throughput Ingestion for Video Warehouse: Comprehensive Configuration and Effective Exploration 2025 SIGMOD 4.9605343e-05
11,299 A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty 2025 VLDB 4.9605343e-05
11,350 AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines 2025 VLDB 4.9605343e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 25 of 25 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061463175
74 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00037164008
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035920657
142 Neo: A Learned Query Optimizer 2019 VLDB 0.00029114937
236 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00023639649
309 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002143249
313 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021288111
320 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021128745
405 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019020138
411 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.0001874043
453 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001801482
458 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017870238
508 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017108973
583 Automatic Performance Diagnosis and Tuning in Oracle 2005 CIDR 0.00015964021
775 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014062388
1,157 P-Store: An Elastic Database System with Predictive Provisioning 2018 SIGMOD 0.00011748784
1,294 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011129451
1,700 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8224761e-05
1,938 Elastic Machine Learning Algorithms in Amazon SageMaker 2020 SIGMOD 9.3316919e-05
2,220 The Case for Predictive Database Systems: Opportunities and Challenges 2011 CIDR 8.8121054e-05
2,572 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.2581875e-05
2,929 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.830745e-05
3,959 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.8804723e-05
4,061 Database-Agnostic Workload Management 2019 CIDR 6.8129772e-05
5,160 Facilitating SQL Query Composition and Analysis 2020 SIGMOD 6.2354336e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

# Overall Rank Paper Year Venue
1 10,653 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD
2 6,464 Towards General and Efficient Online Tuning for Spark 2023 VLDB
3 2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB
4 74 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD
5 1,294 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB
6 2,779 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB
7 2,572 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD
8 3,057 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB
9 5,304 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB
10 309 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD