Development of a data migration tool from SQL databases to Nosql databases

Conventional database management systems normalize the data and host it in the associated tables. Data is stored on disk systems and transferred to memory for processing. Due to today's technological developments, the data stack formed by gathering billions of data in small dimensions is called big data. Processing large stacks in relational databases reduces performance. Therefore, the use of NoSQL systems organizing data for processing in memory has become inevitable. Data obtained from social media and internet of things can be considered as big data. One of the most important issues today is the analysis of data and the extraction of meaningful information. It is inevitable to use NoSQL systems instead of relational database systems in order to save processing time especially for data analytic studies. Businesses that store existing data on relational databases are required to migrate data to NoSQL without loss. In this study, the methods used for data migration from relational database systems to NoSQL systems are discussed, and a method based on the number of foreign keys in the database table is proposed. It has been found that with the software developed using Python language, the proposed method can perform lossless data migration.