Stream Processing
Stream Processing is a data processing paradigm within data engineering and big data analytics that involves the continuous, real-time computation and analysis of unbounded data streams as they are generated, distinguishing it from batch processing by its low-latency, event-driven execution model.
7.1K
Publications
361.9K
Citations
16K
Authors
2.6K
Institutions
Publications per year
2017–2026
2.3K
Variants
Stream Data Processing
7.1K
YOLOX: Exceeding YOLO Series in 2021
Zheng Ge, Songtao Liu, Feng Wang et al. · arXiv (Cornell University) · 2021 · 3K citations · Full text
Models and issues in data stream systems
Brian Babcock, Shivnath Babu, Mayur Datar et al. · 2002 · 2.5K citations
Matei Zaharia, Reynold Xin, Patrick Wendell et al. · Communications of the ACM · 2016 · 2.3K citations
Mining high-speed data streams
Pedro Domingos, Geoff Hulten · 2000 · 2.2K citations · Full text
1–5 of 7.1K
16K
35
h-index
31
h-index
28
h-index
25
h-index
24
h-index
1–5 of 16K
2.6K
Stanford University
Stanford, United States
58 h-index
351 publications
61.5K citations
AT&T (United States)
Bedminster, United States
56 h-index
239 publications
21.6K citations
IBM (United States)
Armonk, United States
51 h-index
386 publications
19.6K citations
University of California, Berkeley
Berkeley, United States
48 h-index
197 publications
45.1K citations
Georgia Institute of Technology
Atlanta, United States
43 h-index
292 publications
13.5K citations
Massachusetts Institute of Technology
Cambridge, United States
41 h-index
236 publications
20.1K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
38 h-index
206 publications
12.4K citations
Tsinghua University
Beijing, China
37 h-index
277 publications
14.2K citations
1–8 of 2.6K
PVLDB · 139 publications · 9.6K citations
54
h-index
TKDE · 93 publications · 7K citations
39
h-index
88 publications · 3.9K citations
36
h-index
TPDS · 58 publications · 2.7K citations
31
h-index
60 publications · 3.3K citations
29
h-index
1–5