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Railgun: managing large streaming windows under MAD requirements

Summary: Railgun: elastic distributed streaming with true long-horizon sliding windows under MAD, avoiding fixed-window shortcuts. Outperforms Flink on latency; scales near-linearly to 1M events/s with ms latency and memory independent of window size. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12700
Venue
VLDB
Year
2021
Pagerank
5.1869874e-05
Overall Rank
9,968 | 31.62%
DOI
10.14778/3476311.3476384

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gomes_vldb21,
        title = {{Railgun: managing large streaming windows under MAD requirements}},
        author = {Gomes, Ana Sofia and Oliveirinha, João and Cardoso, Pedro and Bizarro, Pedro},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {12},
        pages = {3069--3082},
        doi = {10.14778/3476311.3476384},
        url = {https://doi.org/10.14778/3476311.3476384},
        year = {2021}
}

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9,738 GeaFlow: A Graph Extended and Accelerated Dataflow System 2023 SIGMOD 5.227679e-05
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