Foundations of Automated Database Tuning
Summary: Foundations for automating database performance tuning to enable self-managing DBMS. Survey of auto-tuning tools, architectures, algorithms; links self-manageability to resource usage and frames tuning as queueing/optimization; AutoAdmin as a case study. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,812 | Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation | 2022 | VLDB | 6.7373184e-05 |
| 6,151 | An Efficient Transfer Learning Based Configuration Adviser for Database Tuning | 2024 | VLDB | 5.183652e-05 |
| 6,268 | Speedup Your Analytics: Automatic Parameter Tuning for Databases and Big Data Systems | 2019 | VLDB | 5.133857e-05 |
| 10,247 | Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents | 2026 | VLDB | 4.1945683e-05 |
| 10,849 | AXE: A Task Decomposition Approach to Learned LSM Tuning | 2025 | VLDB | 4.1945683e-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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