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In-Browser Interactive SQL Analytics with Afterburner

Summary: Demonstrates a pure JavaScript analytical RDBMS (Afterburner) with in-memory columnar storage and asm.js compilation, no external dependencies. Back-end materializes a view from a predicate-template; shipped to the browser enables fast local querying. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5432
Venue
SIGMOD
Year
2017
Pagerank
5.269408e-05
Overall Rank
9,435 | 35.27%
DOI
10.1145/3035918.3058736

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{gebaly_sigmod17,
        title = {{In-Browser Interactive SQL Analytics with Afterburner}},
        author = {Gebaly, Kareem El and Lin, Jimmy},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3058736},
        url = {https://dl.acm.org/doi/10.1145/3035918.3058736},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
9,419 Language-Agnostic Integrated Queries in a Managed Polyglot Runtime 2021 VLDB 5.273161e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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