gStore: Answering SPARQL Queries via Subgraph Matching
Due to the increasing use of RDF data, efficient processing of SPARQL queries over RDF datasets has become an important issue. However, existing solutions suffer from two limitations: they cannot answer SPARQL queries with wildcards in a scalable manner; and they cannot handle frequent updates in RDF repositories efficiently. Thus, most of them have to reprocess the dataset from scratch. In this paper, the authors propose a graph-based approach to store and query RDF data. Rather than mapping RDF triples into a relational database as most existing methods do, they store RDF data as a large graph. A SPARQL query is then converted into a corresponding subgraph matching query.