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Optimizing the Chase: Scalable Data Integration under Constraints

Summary: Introduces the frugal chase, producing smaller universal solutions while retaining polynomial data complexity. A compact graph-based implementation scales LAV query rewriting under weakly acyclic constraints, accelerating dependency compilation by up to three orders of magnitude. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11072
Venue
VLDB
Year
2014
Pagerank
5.5181056e-05
Overall Rank
7,930 | 45.60%
DOI
10.14778/2733085.2733093

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{konstantinidis_vldb14,
        title = {{Optimizing the Chase: Scalable Data Integration under Constraints}},
        author = {Konstantinidis, George and Ambite, José Luis},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {14},
        doi = {10.14778/2733085.2733093},
        url = {https://doi.org/10.14778/2733085.2733093},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,634 Benchmarking the Chase 2017 PODS 8.3210907e-05
7,867 ForBackBench: A Benchmark for Chasing vs. Query-Rewriting 2022 VLDB 5.5277527e-05
9,228 Enabling Personal Consent in Databases 2022 VLDB 5.3018457e-05
11,366 Bounded Treewidth and the Infinite Core Chase: Complications and Workarounds toward Decidable Querying 2023 PODS 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

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

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