Building OLAP cubes from columnar NoSQL data warehouses

Abstract

The work presented in this paper aims to build OLAP cubes from big data warehouses implemented by using the columnar NoSQL model. The use of NoSQL models is motivated by the inability of the relational model, usually used to implement data warehousing, to allow data scalability easily. Indeed, the columnar NoSQL model is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). Our main contribution is to define a new cube operator called MC-CUBE (MapReduce Columnar CUBE), which allows building columnar NoSQL cubes by taking into account the no relational and distributed aspects when data warehouses are stored.