Implementing Multidimensional Data Warehouses into NoSQL

Abstract

Abstract: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: columnoriented 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 (columnoriented) happens to be faster than MongoDB (document-oriented) in terms of loading time.

Document-Oriented Data Warehouses: Complex Hierarchies and Summarizability

“…The data model that we will propose is inspired by our previous work [3]. It takes into account that document-oriented implementations of data warehouses work better with flat models i.e.…”

“…Document-oriented systems are one of the most popular classes of NoSQL approaches [5]. Data is stored in documents and documents are grouped in collections [5,3]. Documents have a flexible schema.…”

Implementation of Multidimensional Databases in Column-Oriented NoSQL Systems

“…Mapping the multidimensional model to relational databases is quite straightforward, but until now there is no work only an initial attempt in [4]) that considers the direct mapping from the multidime sional conceptual model to NoSQL logical models (see Fig. 1).…”

“…Mapping the multidimensional but until now there is no work [4]) that considers the direct mapping from the multidimen-. NoSQL models are more expressive than relational models i.e.…”

“…Nowadays, research attention has turned towards using these systems for storing "big" data and analyzing it. This work joins substantial ongoing work on the area on the use of NoSQL solutions for data warehousing [4,6,18,19]. In this paper, we focus on one class of NoSQL stores: columnoriented systems such as HBase [11] or Cassandra [13] and inspired by Bigtable [2].…”