Versioning Data During Migration Processes in Cloud Environment

Abstract

Nowadays, big data influences many aspects of human life. They help in medicine with diagnosing different illnesses, in traffic with watching of traffic accidents, and of course, they have a crucial role in supporting decisions. It is appropriate to test another database, respectively, another database type, in every operation's unsatisfactory performance by using a set database. A transformation process is needed in this case. Big Data entering this database has a different structure and size, which influences the set transformation process's time difficulty. The transformation process changes the data structure, from relational to nonrelational, respectively nonrelational to a relational database, making it possible to stop the process or an error that can end up with an incomplete change of a data structure and the data this process must have been repeated. “Version” system we created in this paper is, in the case of incomplete data change, respectively failure of transformation process during the transformation of a relational database to a nonrelational or nonrelational database to relational, capable of continuing from the error point of the previous approach, and so it can erase necessity to perform whole transformation process from the very first beginning.