Foundations of Automated Database Tuning
Summary: Tutorial on the foundations of automated database tuning and self-managing systems, framing performance optimization as a total-cost-of-ownership problem. Unifies mathematical tools, resource/manageability tradeoffs, algorithms, architectures, commercial practice, and academic research. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Surajit Chaudhuri (Microsoft)
- 2. Gerhard Weikum (Max Planck Institute)
BibTeX Citation
@article{chaudhuri_vldb06,
title = {{Foundations of Automated Database Tuning}},
author = {Chaudhuri, Surajit and Weikum, Gerhard},
journal = {PVLDB},
series = {{VLDB} '06},
pages = {1265},
year = {2006}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,770 | Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation | 2022 | VLDB | 8.0343719e-05 |
| 5,284 | An Efficient Transfer Learning Based Configuration Adviser for Database Tuning | 2024 | VLDB | 6.1963031e-05 |
| 5,969 | Speedup Your Analytics: Automatic Parameter Tuning for Databases and Big Data Systems | 2019 | VLDB | 5.9296488e-05 |
| 10,297 | Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents | 2026 | VLDB | 5.0407989e-05 |
| 11,436 | AXE: A Task Decomposition Approach to Learned LSM Tuning | 2025 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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