Exploring the Hybrid Approach: Integrating Relational and Graph Databases for Enhanced Data Management

Relational database models (also called SQL databases) are dominant databases that are designed to handle structured data effectively. Relational databases (RDB) have established themselves as the primary storage solution for most data that supports the web. These databases have a well-documented history of demonstrating scalability, efficient storage, optimized query execution, and reliability. However, with the emergence of social networks and advancements in technology, new demands have arisen, placing greater importance on graph-structured data. The inclusion of huge amounts of data kept in RDB is a fundamental necessity for the evolution of the existing web of documents into a web of data (and, eventually, a semantic web). A program to convert database from a relational to a graph model would prove to be beneficial in this case. Due to the unique characteristics of data and the types of queries involved, both RDB and RGD have their respective powers and limitations. In light of this, the research aims to convert a relational database into a graph database by leveraging the schema. This conversion allows for the utilization of a dual database system through migration. By exploiting the existing schema, data can be converted and transferred from a relational model to a graph model, enabling the benefits and capabilities of both types of databases to be harnessed effectively.