PrefDB: Bringing Preferences Closer to the DBMS

Summary: PrefDB introduces a preference-aware relational model and algebra to express varied preferential queries. Hybrid, non-intrusive to the core, enables operator-level optimizations; PrefDBAdmin aids design, testing, and tuning of preferences. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: hce77f2ca0862d08d
Venue: SIGMOD
Year: 2012
Pagerank: 4.9793485e-05
Overall Rank: 12,611 | 15.22%
DOI: 10.1145/2213836.2213927

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Anastasios Arvanitis (National Technical University of Athens)
2. Georgia Koutrika (IBM)

BibTeX Citation

@inproceedings{arvanitis_sigmod12,
        title = {{PrefDB: Bringing Preferences Closer to the DBMS}},
        author = {Arvanitis, Anastasios and Koutrika, Georgia},
        series = {{SIGMOD} '12},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2213836.2213927},
        url = {https://dl.acm.org/doi/10.1145/2213836.2213927},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
961	RankSQL: Query Algebra and Optimization for Relational Top-k Queries	2005	SIGMOD	0.0001282305
1,377	Preference SQL - Design, Implementation, Experiences	2002	VLDB	0.00010871114

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