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The Future is Big Graphs! A Community View on Graph Processing Systems

Sherif Sakr 1 Angela Bonifati 2, 3, 4 Hannes Voigt 5 Alexandru Iosup 6, 7 Khaled Ammar 8 Renzo Angles 9 Walid Aref 10 Marcelo Arenas 11, 12 Maciej Besta 13 Peter Boncz 14 Khuzaima Daudjee 15 Emanuele Della Valle 16 Stefania Dumbrava 17 Olaf Hartig 18 Bernhard Haslhofer 19 Tim Hegeman 20 Jan Hidders 21 Katja Hose 22 Adriana Iamnitchi 23 Vasiliki Kalavri 24 Hugo Kapp 25 Wim Martens 26 Tamer Özsu 15 Eric Peukert 27 Stefan Plantikow 5 Mohamed Ragab 28 Matei Ripeanu 29 Semih Salihoglu 15 Christian Schulz 30 Petra Selmer 5 Juan Sequeda 31 Joshua Shinavier 32 Gábor Szárnyas 33 Riccardo Tommasini 28 Antonino Tumeo 34 Alexandru Uta 20 Ana Lucia Varbanescu 35 Hsiang-Yun Wu 36 Nikolay Yakovets 37 Da Yan 38 Eiko Yoneki 39
2 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
4 TYREX - Types and Reasoning for the Web
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?
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https://hal.inria.fr/hal-03128601
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Submitted on : Tuesday, February 2, 2021 - 12:29:22 PM
Last modification on : Friday, January 21, 2022 - 3:11:02 AM

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Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup, Khaled Ammar, et al.. The Future is Big Graphs! A Community View on Graph Processing Systems. Communications of the ACM, Association for Computing Machinery, 2021, 64 (9), pp.62-71. ⟨10.1145/3434642⟩. ⟨hal-03128601⟩

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