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PolyFrame: A Retargetable Query-based Approach to Scaling Dataframes

Summary: Retargets AFrame from AsterixDB to a backend-agnostic, query-based layer for scalable DataFrame analytics. Introduces PolyFrame, preserving Pandas API while incrementally shaping queries for diverse composable languages across DBMS backends. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12595
Venue
VLDB
Year
2021
Pagerank
6.5360246e-05
Overall Rank
4,728 | 67.57%
DOI
10.14778/3476249.3476281

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sinthong_vldb21,
        title = {{PolyFrame: A Retargetable Query-based Approach to Scaling Dataframes}},
        author = {Sinthong, Phanwadee and Carey, Michael J.},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {2296--2304},
        doi = {10.14778/3476249.3476281},
        url = {https://doi.org/10.14778/3476249.3476281},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
24 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00054865648
1,015 AsterixDB: A Scalable, Open Source BDMS 2014 VLDB 0.00012647763
1,431 Towards Scalable Dataframe Systems 2020 VLDB 0.00010807221
2,651 Magpie: Python at Speed and Scale using Cloud Backends 2021 CIDR 8.2918086e-05
3,411 Scaling Spark in the Real World: Performance and Usability 2015 VLDB 7.436229e-05
4,292 Putting Pandas in a Box 2021 CIDR 6.7784325e-05
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