Toward automatic generation of column-oriented NoSQL databases in Big Data context

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Abstract

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.

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APA

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, 15(9), 4–16. https://doi.org/10.3991/ijoe.v15i09.10433

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