Relational Database Management Systems (RDBMS) is widely used to store the Data and Information. As we already know RDBMS can store the data in the form of table but if we want to know the complex data relationships and interconnected information, we have to convert the relational database to graph database. Professionals working with airline databases will be able to quickly query highly connected data thanks to graph databases' ability to quickly uncover and manage new and beneficial associations. Relational databases use expensive huge joins to query related data, whereas graph data-stores contain direct references to their neighboring nodes. In order to handle the enormous quantity of airline data being created at a very high pace, scalability was therefore greatly needed. Additionally, the majority of airline data is semi- or un-structured, necessitating a schema-less database. In this paper a methodology to issues that occurs while converting an Airline relational to a graph database. By utilizing the source's restrictions and schema. Conjunctive SQL searches over the source are supported by the method and converted into graphs. procedures that traverse the target. To demonstrate the viability of the solution and the effectiveness of query response across the target database, the experimental outcomes are shown. Nodes are mapped to tuples, while edges are mapped to foreign keys. Constraints were maintained during the change. In order to build the suggested solution, SQL2Neo, popular graph database Neo4j and MySQL as relational databases were both used. Index Terms—Database migration, Graph, data, attributes, Relationships, tables.