Data warehouses in MongoDB vs SQL Server: A comparative analysis of the querie performance

Abstract

Due to its historical nature, data warehouses require that large volumes of data need to be stored in their repositories. Some organizations are beginning to have problems to manage and analyze these huge volumes of data. This is due, in large part, to the relational databases which are the primary method of data storage in a data warehouse, and start underperforming, crumbling under the weight of the data stored. In opposition to these systems, arise the NoSQL databases that are associated with the storage of very large volumes of data inherent to the Big Data paradigm. Thus, this article focuses on the study of the feasibility and the implications of the adoption of a NoSQL database, within the data warehousing context. MongoDB was selected to represent the NoSQL systems in this investigation. In this paper will be explained the processes required to design the structure of a data warehouse and typically dimensional queries in the MongoDB system. The undertaken research culminates in the performance analysis of queries executed in a traditional data warehouse, based on the SQL Server system, and an equivalent data warehouse based on the MongoDB system.