Streaming Data Processing
Streaming Data Processing is a computational paradigm that belongs to the class of data processing methods, distinguished by its capability to continuously ingest, analyze, and transform data streams in real time as they are generated, enabling low-latency decision-making in IoT analytics and reconfigurable accelerator systems.
673
Publications
32.4K
Citations
2.4K
Authors
711
Institutions
Publications per year
2017–2026
255
673
Aurora: a new model and architecture for data stream management
Daniel J. Abadi, Don Carney, Ugur �etintemel et al. · The VLDB Journal · 2003 · 1.5K citations
The Design of the Borealis Stream Processing Engine
Daniel J. Abadi, Yanif Ahmad, Magdalena Bałazińska et al. · 2005 · 1.2K citations
S4: Distributed Stream Computing Platform
Leonardo Neumeyer, Bruce Robbins, Anish Nair et al. · 2010 · 905 citations
Mohamed Medhat Gaber, Arkady Zaslavsky, Shonali Krishnaswamy · ACM SIGMOD Record · 2005 · 887 citations
Amitabha Roy, Ivo Mihailovic, Willy Zwaenepoel · 2013 · 687 citations · Full text
1–5 of 673
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711
IBM (United States)
Armonk, United States
17 h-index
87 publications
5.1K citations
Georgia Institute of Technology
Atlanta, United States
13 h-index
40 publications
1.2K citations
Massachusetts Institute of Technology
Cambridge, United States
12 h-index
38 publications
6.7K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
11 h-index
52 publications
2.9K citations
ETH Zurich
Zurich, Switzerland
9 h-index
20 publications
1.2K citations
Chalmers University of Technology
Gothenburg, Sweden
9 h-index
39 publications
669 citations
Technische Universität Berlin
Berlin, Germany
9 h-index
26 publications
1.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
8 h-index
13 publications
287 citations
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PVLDB · 14 publications · 794 citations
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15 publications · 507 citations
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FGCS · 11 publications · 672 citations
11
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9 publications · 180 citations
9
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8 publications · 244 citations
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