NO-SQL DATABASE X SQL DATABASE

NO-SQL DATABASE X SQL DATABASE: PERFORMANCE STUDY IN LARGE MASSES

Abstract

We are in the era of large bodies of data. Storage and handling large amounts of data is a challenge. There was a time when the databases of the relational model were the only viable solution, by them being safe and easy handling. With technological advances and the popularization of the internet around the world, every moment a considerable number of new data is generated, due to this phenomenon some new data manipulation approaches arise to meet the increasing needs of the market. The NoSQL databases are being increasingly recognized as alternatives to relational model for data manipulation. Both approaches are good for certain situations. This work aims to make a comparative study between relational databases and NoSQL database. Our research compares the two databases to help the developer to identify which platform is best suited for a specific data mass and thus assist in decision-making with respect to what is the best choice for the project in question. The methodology used in this work is the analysis of database architectures and testing involving large masses of data to check the performance of each database. In the results obtained in our research we observed a surprising difference between the MS SQL Server database and the MongoDB in the data inclusion time. Another result that caught our attention was the query time between MongoDB and MSSQL, which proved to be significant for our conclusions about which bank is most recommendable for large requests. We also noticed that there is a difference in the resource consumption of each DBMS, which may influence the choice of one platform.