Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

SQL and NoSQL Databases in the Context of Industry 4.0

Version 1 : Received: 29 October 2021 / Approved: 1 November 2021 / Online: 1 November 2021 (13:01:51 CET)

A peer-reviewed article of this Preprint also exists.

de Oliveira, V.F.; Pessoa, M.A.O.; Junqueira, F.; Miyagi, P.E. SQL and NoSQL Databases in the Context of Industry 4.0. Machines 2022, 10, 20. de Oliveira, V.F.; Pessoa, M.A.O.; Junqueira, F.; Miyagi, P.E. SQL and NoSQL Databases in the Context of Industry 4.0. Machines 2022, 10, 20.

Journal reference: Machines 2021, 10, 20
DOI: 10.3390/machines10010020

Abstract

The data-oriented paradigm has proven to be fundamental for the technological transformation process that characterizes Industry 4.0 (I4.0) so that Big Data & Analytics is considered a technological pillar of this process. The literature reports a series of system architecture proposals that seek to implement the so-called Smart Factory, which is primarily data-driven. Many of these proposals treat data storage solutions as mere entities that support the architecture's functionalities. However, choosing which logical data model to use can significantly affect the performance of the architecture. This work identifies the advantages and disadvantages of relational (SQL) and non-relational (NoSQL) data models for I4.0, taking into account the nature of the data in this process. The characterization of data in the context of I4.0 is based on the five dimensions of Big Data and a standardized format for representing information of assets in the virtual world, the Asset Administration Shell. This work allows identifying appropriate transactional properties and logical data models according to the volume, variety, velocity, veracity, and value of the data. In this way, it is possible to describe the suitability of SQL and NoSQL databases for different scenarios within I4.0.

Keywords

Industry 4.0; Database; Data models; Big Data & Analytics; Asset Administration Shell

Subject

ENGINEERING, Industrial & Manufacturing Engineering

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