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Db2une: Tuning Under Pressure via Deep Learning

Summary: Db2une automatically tunes Db2 knobs by encoding queries with QBERT (transformer-based embeddings) and driving a stability-oriented on-policy deep reinforcement learning agent to balance performance and resource use. Multi-phase, metadata-driven training leverages cost estimates and interpolation to avoid executing queries, enabling scalable tuning of large workloads and outperforming expert and state-of-the-art recommenders. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13589
Venue
VLDB
Year
2024
Pagerank
4.3480651e-05
Overall Rank
9,358 | 34.97%
DOI
10.14778/3685800.3685811

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
8,896 SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation 2026 VLDB 4.4229886e-05
10,217 This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! 2026 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 17 of 17 cited papers.

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

Rank Cited Paper Year Venue Pagerank
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036859633
510 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021420477
517 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00021193179
779 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016719473
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
1,404 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00012179714
1,816 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00010438512
2,050 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 9.6883066e-05
3,800 Why You Should Run TPC-DS: A Workload Analysis 2007 VLDB 6.7529849e-05
3,995 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 6.5475871e-05
4,377 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 6.2331947e-05
4,413 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 6.1989918e-05
4,658 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.0084453e-05
4,730 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 5.9604983e-05
7,126 Guided automated learning for query workload re-optimization 2019 VLDB 4.8184704e-05
7,776 Plan Stitch: Harnessing the Best of Many Plans 2018 VLDB 4.6493147e-05
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510 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021420477
779 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016719473