Implementing Multidimensional Data Warehouses into NoSQL

Max Chevalier, Mohammed El Malki, Arlind Kopliku, Olivier Teste, Ronan Tournier


Not only SQL (NoSQL) databases are becoming increasingly popular and have some interesting strengths such as scalability and flexibility. In this paper, we investigate on the use of NoSQL systems for implementing OLAP (On-Line Analytical Processing) systems. More precisely, we are interested in instantiating OLAP systems (from the conceptual level to the logical level) and instantiating an aggregation lattice (optimization). We define a set of rules to map star schemas into two NoSQL models: column-oriented and document-oriented. The experimental part is carried out using the reference benchmark TPC. Our experiments show that our rules can effectively instantiate such systems (star schema and lattice). We also analyze differences between the two NoSQL systems considered. In our experiments, HBase (column-oriented) happens to be faster than MongoDB (document-oriented) in terms of loading time.


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Paper Citation

in Harvard Style

Chevalier M., El Malki M., Kopliku A., Teste O. and Tournier R. (2015). Implementing Multidimensional Data Warehouses into NoSQL . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 172-183. DOI: 10.5220/0005379801720183

in Bibtex Style

author={Max Chevalier and Mohammed El Malki and Arlind Kopliku and Olivier Teste and Ronan Tournier},
title={Implementing Multidimensional Data Warehouses into NoSQL},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},

in EndNote Style

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Implementing Multidimensional Data Warehouses into NoSQL
SN - 978-989-758-096-3
AU - Chevalier M.
AU - El Malki M.
AU - Kopliku A.
AU - Teste O.
AU - Tournier R.
PY - 2015
SP - 172
EP - 183
DO - 10.5220/0005379801720183