RDF_QDAG in Action: Efficient RDF Data Querying at Scale.

Querying large scale RDF data remains a challenging task, despite the development of several approaches to manage this type of data. Indeed, the "Schemaless" nature of this data prevents from taking advantage of the optimization techniques developed by the database community for decades. Recently, we introduced RDF_QDAG, a new data management system for RDF, that relies on physical predicate-oriented fragmentation and logical graph exploration. RDF_QDAG offers a good compromise between scalability and performance. It also enables spatial queries to be processed thanks to a suitable extension that improves not only data access but also query evaluation. In this demonstration, we present through a comprehensible GUI the main features and enhancements of RDF_QDAG. We assist the user in the formulation of queries, and also the interpretation of results according to the type (spatial, graph patterns, etc.) of data processed. We also show the different optimization techniques offered and their impact on performance. We also give the user the possibility to compare RDF_QDAG with a well known and commonly used RDF data management system.