Comparative Analysis of Relational Databases and Graph Databases

Abstract

Relational model has been dominating the computer industry since the 1980s mainly for storing and retrieving data. Lately, however, relational database is losing its importance due to its dependence on a rigid schema which makes it difficult to add new relationships between the objects. Another important reason of its failure is that generally, the relational model works best when there are a relatively small and static number of relationships between objects. It has long been a tricky problem in the relational databases to work with dynamic, recursive or complex relationships. To add on to these problems, the global rapid development and maturing of Internet prompted the exploding increase of information in each field and provided people with abundant sources for seeking and obtaining useful information. This huge repository of unstructured data has resulted in making the data search and knowledge extraction, a very cumbersome task if one continues using the legacy relational databases. One of the proposed solutions is to shift to the graph databases as they aspire to overcome such type of problems. Graph databases not only makes it easier to store and retrieve data for the World Wide Web but also provide relevant and streamlined search results from the abundant information present on the internet comparatively faster than relational databases. This thesis provides a comparative analysis of a graph database Neo4j with the most prevalent relational database MySQL.