A Model-Driven Engineering: From Relational Database to Document-oriented Database in Big Data Context

In today's world multiple players in digital technology produce infinite amounts of data. Sensors, social networks or e-Commerce, they all generate information that is incremented in real time according to Gartner's 5V: in Volume, Velocity, Variety, Value, and Veracity. The digital transformation of companies leads an evolution of databases towards Big Data whose power has become increasingly strategic. The exploitation of the data is a key to a better understanding and management of the company and its markets. This obviously imposes an ability to generate data, to store it, to give it meaning and then to exploit it. At the same time, the modernization of the Big Data platform is essential to automate this process. In this paper, we explain how to design and apply transformation rules to transfer from an SQL relational database to a Big Data solution within NoSQL. For this, we use the Model Driven Architecture and the transformation languages as MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) and Acceleo for describing the meta-models for the development of transformation model. The transformation rules defined in this work can generate, from the class diagram, a JSON files for creation document-oriented NoSQL database.