Query-based Performance Comparison of Graph Database and Relational Database

A graph database is a type of NoSQL database that uses graph structure for semantic queries with nodes, edges, and properties to represent and store data. It has been applied in many fields, such as education, health, business, and social network, with many famous applications such as Google, Facebook, and eBay. One of the main advantages of the graph database is its effective performance in data queries. This paper presents a comprehensive comparison of the performance based on the execution time of a NoSQL graph database named Neo4J with a popular relational database system, MySQL, which is used as the underlying technology in developing a software system. Query types are categorized into four groups: selection/ search, recursion, aggregation, and pattern matching. We examined representative questions for each group and executed them on Neo4j and MySQL using a real-life dataset named Career Village. The results show that Neo4j’s data query performance is better than MySQL in most results.