Foundations of Automated Database Tuning

Summary: Foundational framework for automated DB tuning using queuing theory and combinatorial optimization to model self-manageability in DBMS. A resource-aware evaluation approach to compare technologies, reveal implicit assumptions, and connect manageability to memory/index usage, with design implications and prior-work survey. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3794
Venue: SIGMOD
Year: 2005
Pagerank: 5.1698206e-05
Overall Rank: 10,047 | 31.07%
DOI: 10.1145/1066157.1066305

Incoming Non-self Citations Over Time

Authors

1. Surajit Chaudhuri (Microsoft)
2. Gerhard Weikum (Max Planck Institute)

BibTeX Citation

@inproceedings{chaudhuri_sigmod05,
        title = {{Foundations of Automated Database Tuning}},
        author = {Chaudhuri, Surajit and Weikum, Gerhard},
        series = {{SIGMOD} '05},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1066157.1066305},
        url = {https://dl.acm.org/doi/10.1145/1066157.1066305},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,766	Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty	2022	VLDB	6.094771e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
6,700	Self-Managing Technology in Database Management Systems	2004	VLDB	5.7981065e-05

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