Toward Automatic Generation of Column-Oriented NoSQL Databases in Big Data Context


  • Redouane Esbai Mohammed First University
  • Fouad Elotmani Mohammed First University
  • Fatima Zahra Belkadi Mohammed First University



SQL relational database, NoSQL, MDA, The transformation rules, Big Data, CQL


The growth of application architectures in all areas (e.g. Astrology, Meteorology, E-commerce, social network, etc.) has resulted in an exponential increase in data volumes, now measured in Petabytes. Managing these volumes of data has become a problem that relational databases are no longer able to handle because of the acidity properties. In response to this scaling up, new concepts have emerged such as NoSQL. In this paper, we show how to design and apply transformation rules to migrate from an SQL relational database to a Big Data solution within NoSQL. For this, we use the Model Driven Architecture (MDA) and the transformation languages like as MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) and Acceleo which define the meta-models for the development of transformation model. The transformation rules defined in this work can generate, from the class diagram, a CQL code for creation column-oriented NoSQL database.

Author Biography

Redouane Esbai, Mohammed First University

teaches the concept of Information System at Mohammed 1 University. He got his thesis of national doctorate in 2012. He got a degree of an engineer in Computer Sciences from the National School of Applied Sciences at Oujda. He received his M.Sc. degree in New Information and Communication Technologies from the faculty of sciences and Techniques at Sidi Mohamed Ben Abdellah University. His activities of research in the MASI Laboratory (Applied Mathematics and Information System) focusing on MDA (Model Driven Architecture) integrating new technologies XML, Spring, Struts, GWT, etc.




How to Cite

Esbai, R., Elotmani, F., & Belkadi, F. Z. (2019). Toward Automatic Generation of Column-Oriented NoSQL Databases in Big Data Context. International Journal of Online and Biomedical Engineering (iJOE), 15(09), pp. 4–16.