Bridging the gap for retrieving DBpedia data

DBpedia is nowadays considered one of the main projects in the World Wide Web that extracts and enriches Wikipedia data in a structured form. Also, it is considered the central hub for the Linked Open Data. Querying DBpedia using big data approaches such as Hive-QL is regarded as one of the new techniques to solve the shortcomings of SPARQL; the main query language of DBpedia and the Semantic Web. Nevertheless, despite the speed of Hive-QL compared to SPARQL, it has a stability problem. Our paper presents a new architecture and implementation for querying DBpedia using Shark query language in addition to Hive-QL. As a result of this work, An obvious decrease in execution time, as well as, an increase in the degree of stability have been attained.