BINARY: A framework for big data integration for ad-hoc querying

Enormous amounts of data are generated everyday of both structured and unstructured nature. Regardless of their differences, data sources must be used in tandem in any effective big data operation. This paper proposes a Software as a Service (SaaS) framework called BINARY which provides a back-end infrastructure for ad-hoc querying, accessing, visualizing and joining data from different data sources such as Relational Database Management Systems like MySQL and big data storage systems like Apache Hive. BINARY is extendable and allows adding other storage engines (e.g. HBase) and analytics engines (e.g. R) as needed. A REST software architecture is used in the framework to enable loose connections between the engines and user interface programs to facilitate their independent updates without affecting the data infrastructure. Our approach is validated with a proof-of-concept prototype implemented on the OpenStack cloud system.