SPARQL in the cloud using Rya

• We build a scalable RDF data management system in a cloud environment.
• Rya is based on Accumulo columnar store and OpenRDF Sesame framework.
• We used 3 indexed tables, SPO, POS, OSP, with triple data stored in the row ID.
• We implemented performance enhancements to scale to billions of triples and milliseconds query time for most queries.
• Rya provides fast and easy access to the data through SPARQL.

SPARQL is the standard query language for Resource Description Framework (RDF) data. RDF was designed with the initial goal of developing metadata for the Internet. While the number and the size of the generated RDF datasets are continually increasing, most of today's best RDF storage solutions are confined to a single node. Working on a single node has significant scalability issues, especially considering the magnitude of modern day data. In this paper we introduce Rya, a scalable RDF data management system that efficiently supports SPARQL queries. We introduce storage methods, indexing schemes, and query processing techniques that scale to billions of triples across multiple nodes, while providing fast and easy access to the data through conventional query mechanisms such as SPARQL. Our performance evaluation shows that in most cases, our system outperforms existing distributed RDF solutions, even systems much more complex than ours.