Performance evaluation of SQL and MongoDB databases for big e-commerce data

With the advent of big data phenomenon in the world of data and its related technologies, the developments on the NoSQL databases are highly regarded. It has been claimed that these databases outperform their SQL counterparts. The aim of this study is to investigate the claim by evaluating the document-oriented MongoDB database with SQL in terms of the performance of common aggregated and non-aggregate queries. We designed a set of experiments with a huge number of operations such as read, write, delete, and select from various aspects in the two databases and on the same data for a typical e-commerce schema. The results show that MongoDB performs better for most operations excluding some aggregate functions. The results can be a good source for commercial and non-commercial companies eager to change the structure of the database used to provide their line-of-business services.