Scalability and Performance Evaluation of Graph Database Systems: A Comparative Study of Neo4j, JanusGraph, Memgraph, NebulaGraph, and TigerGraph

This paper presents a comprehensive analysis and evaluation of the performance and scalability characteristics of graph databases. The study focuses on the leading graph databases, namely Neo4j, JanusGraph, MemGraph, Nebula-Graph, and TigerGraph, as ranked by DB-Engines. In the face of the ever-increasing daily data volumes, traditional database management systems (DBMS) are struggling to cope with the growth, necessitating the exploration of alternative solutions. Graph databases, along with other types such as document and key-value databases, have emerged as promising alternatives that may offer more efficient handling of data-related challenges faced by DBMS.The objective of this research is to evaluate and compare the performance and scalability of these graph databases using various metrics, including query response time, data loading time, and memory usage. Through our experimentation, we have obtained compelling results. Among the top-five graph databases considered, Neo4j has exhibited superior performance, especially when handling larger datasets. It has consistently outperformed the other engines, showcasing its potential as a robust and efficient solution for managing graph-based data.