Abstract
Native RDF (http://www.w3.org/RDF/) stores have been making enormous progress in closing the performance gap compared to relational database management systems (RDBMS). But this small gap, however, still prevents the adoption of RDF stores in scenarios for large-scale enterprise applications. We solve this problem with our native RDF store QUAD and its fundamental design principles. It is based on a vector database schema for quadruples and it is realized by facilitating various index data structures. QUAD also comprises approaches to optimize the SPARQL query execution plan by using heuristic transformations. In this short paper, we briefly introduce QUAD and sketch in which tasks of the Mighty Storage Challenge we will attend to benchmark the current performance capabilities.
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