Graph vs Relational Databases

First of all lets just discuss about Relational and Graph database solution.

Graph Database versus Relational Database:

The above image explains how graph or relational databases work. Major differences between both include data modeling, relationships, querying and performance. All in all, the decision completely depends upon the dataset or the requirements. Graph databases are more appropriate for dealing with interconnected and complex information connections, while relational databases data sets succeed at overseeing organized information effectively.

Following is the one example of graph database schema using Bitnine’s AG Cloud.

Graph databases use graph query languages (G.Q.L) for managing the database. Cypher is one of the main GQL for Graph DBs.

There can be multiple advantages and some disadvantages of Cypher queries, you guys can check below

One of the product AGE Viewer is the best example of using cypher queries with graphical representation of data.

The above figure shows the relationship between Nodes and edges. Query is defined for getting drivers of specific cars.

CONCLUSION:

At the end I conclude, graph databases are better suited for handling complex relationships and interconnected data, while relational databases excel at managing structured data efficiently.