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The generation of RDF data has accelerated to the point where many data sets need to be partitioned across multiple machines in order to achieve reasonable performance when querying the data. Although tremendous progress has been made in the Semantic Web community for achieving high performance data management on a single node, current solutions that allow the data to be partitioned across multiple machines are highly inefficient. In this paper, the authors introduce a scalable RDF data management system that is up to three orders of magnitude more efficient than popular multinode RDF data management systems.
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