The future is big graphs
A CommunityView on Graph Processing Systems
Sherif Sakr (University of Tartu)
Angela Bonifati (Université de Lyon)
Hannes Voigt (neo4j)
A. Iosup (TU Delft - Data-Intensive Systems, Vrije Universiteit Amsterdam)
Khaled Ammar (Borialis Ai)
Renzo Angles (University of Talca)
Walid Aref (Purdue University)
Marcelo Arenas (Puc and Imfd)
MacIej Besta (ETH Zürich)
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Abstract
Graphs are ubiquitous abstractions enabling reusable computing tools for graph processing with applications in every domain. Diverse workloads, standard models and languages, algebraic frameworks, and suitable and reproducible performance metrics will be at the core of graph processing ecosystems in the future. Academics, start-ups, and big tech companies such as Google, Face book, and Microsoft have introduced various systems for managing and processing the growing presence of big graphs. An increasing number of use cases revealed RDBMS performance problems in managing highly connected data, motivating various startups and innovative products, such as Neo4j, Sparksee, and the current Amazon Neptune. Microsoft Trinity along with Azure SQL DB have provided an early distributed database-oriented approach to big graph management.
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