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Speeding up Database Applications with Pyxis

Summary: Pyxis partitions app code via program analysis, moving work to the DB server, cutting latency. Dynamic migration via runtime monitoring with a partitioning tool and live visuals; avoids stored procedures and beats embedded-SQL baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4737
Venue
SIGMOD
Year
2013
Pagerank
6.0317837e-05
Overall Rank
5,949 | 59.19%
DOI
10.1145/2463676.2465265

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{cheung_sigmod13,
        title = {{Speeding up Database Applications with Pyxis}},
        author = {Cheung, Alvin and Madden, Samuel and Arden, Owen and Myers, Andrew C.},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465265},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465265},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

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

Rank Cited Paper Year Venue Pagerank
2,941 Automatic Partitioning of Database Applications 2012 VLDB 7.937125e-05
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