Abstract. Ontologies are pervading many areas of knowledge representation and management. To date, most research efforts have been spent on the development of sufficiently expressive languages for the representation and querying of ontologies; however, querying efficiency has received attention only recently, especially for ontologies referring to large amounts of data. In fact, it is still uncertain how reasoning tasks will scale when applied on massive amounts of data. This work is a first step toward this setting: based on a previous result showing that the SPARQL query language can be mapped to a Datalog, we show how efficient querying of big ontologies can be accomplished with a database oriented extension of the well known system DLV, recently developed. We report our initial results and we discuss about benefits of possible alternative data structures for representing RDF graphs in our architecture.