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)
Incoming Non-self Citations Over Time
Authors
- 1. Ana Sofia Gomes (Feedzai)
- 2. João Oliveirinha (Feedzai)
- 3. Pedro Cardoso (Feedzai)
- 4. Pedro Bizarro (Feedzai)
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}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,738 | GeaFlow: A Graph Extended and Accelerated Dataflow System | 2023 | SIGMOD | 5.227679e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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