Converting Relational Database Into The Graph Database Though The Web Application

Data is playing a big role in our daily life.We are connecting to the data every day,at home,in the car,in our offices.Day by day data is growing which is coming from many different sources.Big data is a term that describes the large volume of data – both structured and unstructured.SQL databases,which popularity coming from several years,time by time losing their leadership,because of Big Data.Such databases,which are part of relational model are Microsoft Access and SQL databases.It's an actual topic for DBA(Database Administrator)to how to handle a huge volume of data,which is coming from many different sources,such as Online Social Network(OSN),Telecommunication,Health care and etc.It's a hard task to generate it,especially when we are using relational databases,which does not supports un-structured data and poor for handling scalability and complexity.Many researches and DBA's start thinking,how to solve this provoke.Some of them already shifted another database,which are oriented more for scalability,flexibility and complexity.No SQL database management system offers more flexible ways to solve Big Data problems.Several ways were proposed,how to transform data from Relational database to NOSQL databases,including: schema mapping,data loading,REST API,batch importer and etc.In this thesis,methodology about improving already existing algorithm will be proposed,which translates database from relational to the graph database.For that,I have created a web application,which provides environment for implementation and testing,also it shows effectiveness of the approach,which I called 1-click method.Web application supports feasibility of translation database from MYSQL to Neo4 J and it provides easy way to convert database from My SQL to Neo4 j.The approach also supports the translation from SQL queries into the Cypher.Query execution comparison will be shown as a result in milliseconds.