Stateful Stream Processing
Stateful Stream Processing is a stream processing paradigm that maintains and updates application state across consecutive data events, enabling computations to depend on historical data and context beyond individual events.
47
Publications
2.9K
Citations
145
Authors
72
Institutions
Publications per year
2017–2026
21
Parents
47
Shadi A. Noghabi, Kartik Paramasivam, Yi Pan et al. · Proceedings of the VLDB Endowment · 2017 · 257 citations
Jin Li, Kristin Tufte, Vladislav Shkapenyuk et al. · Proceedings of the VLDB Endowment · 2008 · 177 citations
Benchmarking Distributed Stream Data Processing Systems
2018 · 161 citations · Full text
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Technische Universität Berlin
Berlin, Germany
5 h-index
11 publications
822 citations

Delft University of Technology
Delft, The Netherlands
3 h-index
3 publications
285 citations
National University of Singapore
Singapore, Singapore
3 h-index
5 publications
266 citations

Imperial College London
London, United Kingdom
3 h-index
8 publications
1.2K citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
2 h-index
4 publications
395 citations

Portland State University
Portland, United States
2 h-index
5 publications
735 citations
University of Potsdam
Potsdam, Germany
2 h-index
1 publications
49 citations

South Ural State University
Chelyabinsk, Russia
2 h-index
6 publications
165 citations
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PVLDB · 4 publications · 479 citations
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3 publications · 298 citations
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Repository · 2 publications · 74 citations
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TKDE · 1 publications · 312 citations
1
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1 publications · 12 citations
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