RDF (Resource Description Framework) is seeing rapidly increasing adoption, for example, in the context of the Linked Open Data (LOD) movement and diverse life sciences data publishing and integration projects. This paper discusses how we have adapted OpenLink Virtuoso, a general purpose RDBMS, for this new type of workload. We discuss adapting Virtuoso’s relational engine for native RDF support with dedicated data types, bitmap indexing and SQL optimizer techniques. We further discuss scaling out by running on a cluster of commodity servers, each with local memory and disk. We look at how this impacts query planning and execution and how we achieve high parallel utilization of multiple CPU cores on multiple servers. We present comparisons with other RDF storage models as well as other approaches to scaling out on server clusters. We present conclusions and metrics as well as a number of use cases, from DBpedia to bio informatics and collaborative web applications.