Distributed RDF Triple Store Using HBase and Hive

The growth of web data has presented new challenges regarding the ability to effectively query RDF data. Traditional relational database systems efficiently scale and query distributed data. With the development of Hadoop its implementation of the MapReduce Framework along with HBase, a NoSQL data store, the semantics of processing and querying data has changed. Given the existing structure of SPARQL, we devised and are continuing to develop a means to query RDF data effectively. By using HBase as a data store and HiveQL as the query generator, we implement a prototype intermediate translator which will generate HiveQL given a SPARQL query. This HiveQL query will then return data from our distributed HBase store.