The Future is Big Graphs! A Community View on Graph Processing Systems
Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup, Khaled, Ammar, Renzo Angles, Walid Aref, Marcelo Arenas, Maciej Besta, Peter A., Boncz, Khuzaima Daudjee, Emanuele Della Valle, Stefania Dumbrava, Olaf, Hartig, Bernhard Haslhofer, Tim Hegeman, Jan Hidders, Katja Hose
TL;DR
This paper discusses the importance of big graphs and community perspectives in shaping future graph processing systems to handle increasingly complex interconnected data.
Contribution
It offers a community-based view on the future challenges and necessary developments for big graph processing systems.
Findings
Identifies key challenges for big graph processing in the next decade.
Highlights the need for new abstractions and system designs.
Emphasizes community collaboration for future advancements.
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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