OUTCOME ANALYSIS USING NEO4J GRAPH DATABASE
Databases are an integral part of a computing system and users heavily rely on the services they provide. When interact with a computing system, we expect that data be stored for future use, that the data is able to be looked up fastly, and we can perform complex queries against the data stored in the database. Many different emerging database types available for use such as relational databases, object databases, keyvalue databases, graph databases, and RDF databases. Each type of database provides unique qualities that have applications in certain domains. Our work aims to investigate and compare the performance and scalability of relational databases to graph databases in terms of handling multilevel queries such as finding the impact of a particular subject with the working area of pass out students. MySQL was chosen as the relational database, Neo4j as the graph database.