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Many applications rely on network analysis to extract business intelligence from large datasets, requiring specialized graph tools such as processing frameworks (e.g. Apache Giraph, Gradoop), database systems (e.g. Neo4j, JanusGraph) or applications/libraries (e.g. NetworkX, nvGraph). A recent survey reports scalability, particularly for loading, as the foremost practical challenge faced by users. In this paper we consider the design space of tools for efficient and scalable graph bulk loading.dblp:conf/gvd/DurandMPS18 fatcat:joffwprfozf4bdpiqbwzuh2hvi