Automatic Extraction of a Document-oriented NoSQL Schema

Fatma Abdelhedi, Fatma Abdelhedi, Amal Ait Brahim, Hela Rajhi, Rabah Tighilt Ferhat, Gilles Zurfluh

2021

Abstract

The NoSQL systems make it possible to manage Databases (DB) verifying the 3Vs: Volume, Variety and Velocity. Most of these systems are characterized by the property schemaless which means absence of the data schema when creating a DB. This property provides undeniable flexibility by allowing the schema to evolve while the DB is in use; however, it is a major obstacle for developers and decision makers. Indeed, the expression of queries (SQL type) requires precise knowledge of this schema. In this article, we provide a process for automatically extracting the schema from a NoSQL document-oriented DB. To do this, we use the MDA (Model Driven Architecture). From a NoSQL DB, we propose transformation rules to generate the schema. An experiment of the extraction process was carried out on a medical application.

Paper Citation

in Harvard Style

Abdelhedi F., Brahim A., Rajhi H., Ferhat R. and Zurfluh G. (2021). Automatic Extraction of a Document-oriented NoSQL Schema. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 192-199. DOI: 10.5220/0010433501920199

in Bibtex Style

@conference{iceis21,
author={Fatma Abdelhedi and Amal Brahim and Hela Rajhi and Rabah Ferhat and Gilles Zurfluh},
title={Automatic Extraction of a Document-oriented NoSQL Schema},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={192-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010433501920199},
isbn={978-989-758-509-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Automatic Extraction of a Document-oriented NoSQL Schema
SN - 978-989-758-509-8
AU - Abdelhedi F.
AU - Brahim A.
AU - Rajhi H.
AU - Ferhat R.
AU - Zurfluh G.
PY - 2021
SP - 192
EP - 199
DO - 10.5220/0010433501920199