A promising method for efficiently querying RDF data consists of translating SPARQL queries into efficient RDBMS-style operations. However, answering SPARQL queries requires handling RDF reasoning, which must be implemented outside the relational engines that do not support it. We introduce the expressive database (DB) fragment of RDF for which we devise novel sound and complete techniques for answering Basic Graph Pattern (BGP) queries. Our techniques explore the two established approaches for handling RDF semantics, namely reformulation and saturation; we show how they cope with updates, a complex problem due to the rich RDF semantics. Our algorithms can be deployed on top of any RDBMS(-style) engine, and we experimentally study their performance trade-offs.
