SQL & NOSQL DATABASE COMPARISON BY CASE DESIGNING AFFILIATE SYSTEM REPORT

Abstract

Nowadays, due to the rapid development of social networks and the blogger culture, there is a tendency to use affiliate systems to promote their product. The Affiliate Reporting Service is a service offered to customers who want to analyze the affiliate systems' performance data. These systems are used by business executives and business owners to analyze ecommerce data and convert it into profit/expense data to adjust their business path further. This type of service includes data storage for all affiliates, data archive management, conversion of advertising campaigns, trend tracking, and more. These systems are based on large data sets that need to be stored correctly and safely stored and processed using database management systems. There are two major direction: SQL and NoSQL, relational and non-relational databases. The differences between them are how they are designed, what types of data they support, how they store information, how they support information security. A rigid relational database schema helps maintain the security and integrity of data when stored and modified. The lack of a rigid database schema and the need to change the entire structure of the table with a minimal change in the storage concept, make it easier to work with non-relational databases and subsequently support them, but it also has its disadvantages. It is important to understand that the tasks are different and the methods for solving them are also different; Choosing a database and database management system is a complex multiparameter task and is one of the most important steps in developing such applications. Properly selected database will reduce the monetary and time costs associated with the development of the software, as well as facilitate system support in the future. The purpose of the article is to compare relational and non-relational databases by different metrics used in Affiliate Reporting Systems Design. In particu-lar, a performance analysis was conducted on the performance of various operations, on the basis of which conclusions were drawn about the use of a particular database.