Document-oriented data warehouses: models and extended cuboids

Max Chevalier (1, 2) , Mohammed El Malki (1, 3) , Arlind Kopliku (1) , Olivier Teste (1, 4) , Ronan Tournier (1, 5)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT3 - Université Toulouse III - Paul Sabatier
3 Capgemini
4 UT2J - Université Toulouse - Jean Jaurès
5 UT Capitole - Université Toulouse Capitole

Within the Big Data trend, there is an increasing interest in Not-only-SQL systems (NoSQL). These systems are promising candidates for implementing data warehouses particularly due to the data structuration/storage possibilities they offer. In this paper, we investigate data warehouse instantiation using a document-oriented system (a special class of NoSQL systems). On the one hand, we analyze several issues including modeling, querying, loading data and OLAP cuboids. We compare document-oriented models (with and without normalization) to analogous relational database models. On the other hand, we suggest improvements in order to benefit from document-oriented features. We focus particularly on extended versions of OLAP cuboids that exploit nesting and arrays. They are shown to work better on workloads with drill-down queries. Research in this direction is new. As existing work focuses on feasibility issues, document-specific implementation features, modeling and cross-model comparison.

Mots clés: NoSQL; Big data warehouse; Document-oriented system; OLAP cuboid

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Max Chevalier, Mohammed El Malki, Arlind Kopliku, Olivier Teste, Ronan Tournier. Document-oriented data warehouses: models and extended cuboids. 10th International IEEE Conference on Research Challenges in Information Science (RCIS 2016) co-located witht the 34th French Conference INFORSID, Jun 2016, Grenoble, France. pp. 13-14. ⟨hal-01474901⟩