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Toward Practical Query Pricing with QueryMarket

Summary: QueryMarket enables practical data-market pricing with an ILP-based formulation for a query class, building on Koutris et al. Uses history to avoid double charging and updates; fair revenue sharing among sellers; prototype validates performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4804
Venue
SIGMOD
Year
2013
Pagerank
8.209612e-05
Overall Rank
2,719 | 81.35%
DOI
10.1145/2463676.2465335

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{koutris_sigmod13,
        title = {{Toward Practical Query Pricing with QueryMarket}},
        author = {Koutris, Paraschos and Upadhyaya, Prasang and Balazinska, Magdalena and Howe, Bill and Suciu, Dan},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465335},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465335},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,576 Data Markets in the Cloud: An Opportunity for the Database Community 2011 VLDB 0.00010317008
2,342 Query-Based Data Pricing 2012 PODS 8.7217471e-05
4,521 How to Price Shared Optimizations in the Cloud 2012 VLDB 6.6468071e-05
6,036 QueryMarket Demonstration: Pricing for Online Data Markets 2012 VLDB 5.9995474e-05
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