A Demonstration of the OtterTune Automatic Database Management System Tuning Service
Summary: OtterTune automatic DBMS knob tuning service leverages historical tuning data and ML models to predict effective configurations. In a demonstration, OtterTune automatically selects configurations that improve DBMS performance, rivaling or beating human experts and existing tools. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bohan Zhang
- 2. Dana Van Aken
- 3. Justin Wang
- 4. Tao Dai
- 5. Shuli Jiang
- 6. Jacky Lao
- 7. Siyuan Sheng
- 8. Andrew Pavlo
- 9. Geoffrey J. Gordon
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 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 |
| 340 | OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases | 2014 | VLDB | 0.00026841628 |
| 424 | Tuning Database Configuration Parameters with iTuned | 2009 | VLDB | 0.00023616398 |
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