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Journal Articles Communications of the ACM Year : 2021

The future is big graphs: a community view on graph processing systems

1 Institute of Computer Science [University of Tartu, Estonie]
2 BD - Base de Données
3 LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
4 TYREX - Types and Reasoning for the Web
5 Neo4j
6 VU - Vrije Universiteit Amsterdam [Amsterdam]
7 TU Delft - Delft University of Technology
8 Universidad de Talca
9 Purdue University [West Lafayette]
10 IMFD - Millennium Institute for Foundational Research on Data
11 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
12 CWI - Centrum Wiskunde & Informatica
13 University of Waterloo [Waterloo]
14 IP Paris - Institut Polytechnique de Paris
15 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
16 ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise
17 LIU - Linköping University
18 AIT - Austrian Institute of Technology [Vienna]
19 Birkbeck College [University of London]
20 AAU - Aalborg University [Denmark]
21 USF - University of South Florida [Tampa]
22 BU - Boston University [Boston]
23 Oracle Labs Switzerland
24 Universität Bayreuth
25 Leipzig University / Universität Leipzig
26 University of Tartu
27 UBC - University of British Columbia
28 Universität Heidelberg [Heidelberg] = Heidelberg University
29 data.world
30 BME - Budapest University of Technology and Economics [Budapest]
31 PNNL - Pacific Northwest National Laboratory
32 UvA - University of Amsterdam [Amsterdam] = Universiteit van Amsterdam
33 TU Wien - Institute of Applied Physics [Vienna]
34 TU/e - Eindhoven University of Technology [Eindhoven]
35 UAB - University of Alabama at Birmingham [ Birmingham]
36 CAM - University of Cambridge [UK]
Hannes Voigt
  • Function : Author
Khaled Ammar
  • Function : Author
Emanuele Della Valle
  • Function : Author
Stefan Plantikow
  • Function : Author
Petra Selmer
  • Function : Author
Juan F. Sequeda
  • Function : Author
Joshua Shinavier
  • Function : Author
Riccardo Tommasini
  • Function : Author
  • PersonId : 1273255
  • IdHAL : rictomm

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?

Dates and versions

hal-03128601 , version 1 (02-02-2021)

Identifiers

Cite

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, 2021, 64 (9), pp.62-71. ⟨10.1145/3434642⟩. ⟨hal-03128601⟩
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