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Keep Your Distributed Data Warehouse Consistent at a Minimal Cost

Summary: Delivers eventual consistency in distributed data warehouses by pruning downstream updates via dependency graphs and post-state data. Frames cost-freshness as a dynamic programming problem and reports a 25% drop in update requests in YouTube's warehouse, enabling heterogeneous deployments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6755
Venue
SIGMOD
Year
2023
Pagerank
5.1650158e-05
Overall Rank
10,063 | 30.96%
DOI
10.1145/3589770

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{xu_sigmod23,
        title = {{Keep Your Distributed Data Warehouse Consistent at a Minimal Cost}},
        author = {Xu, Zhichen and Gao, Ying and Davidson, Andrew},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589770},
        url = {https://dl.acm.org/doi/10.1145/3589770},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,686 TDSQL: Tencent Distributed Database System 2024 VLDB 5.5676271e-05
11,000 Unlocking the Power of CI/CD for Data Pipelines in Distributed Data Warehouses 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

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