If you are working with data, you might have always used a tabular structure of data. In tabular structure, we have a lot of tables that are interconnected with the use of Primary keys and secondary keys. Data follows a structure of Rows and Columns. This is the efficient way of storing data but when we have to run a query that requires use of various columns from various table, query starts to become complex and lengthy. We starts with writing details about a lot of joins , table name , etc and query ends up beacoming complex to read and understand.
From past few days, i come across a new way of storing and querying data, which is known as Graph Database. There are some tools present that helps to change the entire process of how we store data and query it. One such tool is Neo4j. Using any existing Table format table, we can load it in Neo4j using cypher queries. in Graph Database, entire structure of data is change and stored in nodes and relationship manner, where the need of table names cease to exist. Nodes are joined with relationships and each data point is connected with all of its related information in a series of nodes and relationship structure. Compared to Tabular structure of database, graph queries does not requires writing joining condition again and again whenever you require to fetch data. So exploring graph database might be a good activity.