Fast In-Memory Reasoner for Oracle NoSQL Database EE: Uncover hidden relationships that exist in your enterprise data

Graph databases and NoSQL databases, two very important topics in Big Data, have gained popularity in recent years due to their unique characteristics in their horizontally scale-out capability and flexible schema or schema-free design. The recent release of OWL-DBC , an adaptor between Oracle Spatial and Graph 2 and the TrOWL reasoner [2, 1], has built a tight integration between one of the leading industrial graph databases and the cutting edge, in-memory, semantic reasoner to achieve high quality and efficient semantic reasoning on large scale enterprise data. In this session we present OWL-NOSQL, which enhances the Oracle NoSQL Database EE 3 with efficient in-memory reasoning capability from TrOWL. With OWL-NOSQL, users are able to manage their enterprise data in the form of RDF Graph stored in Oracle NoSQL Database EE and gain insight into their data through powerful semantic reasoning. Oracle NoSQL Database EE is a horizontally scaled, key-value database for Web services and cloud. This system uses a simplistic key-value pair data model to achieve efficiency and high scalability. Despite of its simplicity, such a data model can be engineered to represent rather complex knowledge and structures in data, including RDF graphs and OWL ontologies. In fact, key-value pair databases have emerged as one of the promising solutions for semantic exploitation in recent years. Such flexibility enables Oracle NoSQL Database EE to expose its data to external semantic applications, including semantic reasoners, to uncover hidden relationships in the stored data, especially those represent semantic annotations. More concretely, such a semantic extension of Oracle NoSQL Database EE is performed as follows: