17 May Introduction to NoSQL Graph Database

The NoSQL graph database is a technology used for data management. It was invented to control very large sets of structured, semi-structured or unstructured data. It is also a type of database used to represent data in the form of a graph and consists of three components: nodes, relationships, and properties. These components can be used to model the data.

Let’s look at the different examples of Graph Databases softwares such as Graph base,Neo4j, Oracle NoSQL DB etc.

Each of these components are explained below;

• Nodes: The node can be used to represent objects or instances. We can group the nodes by applying a label to each member.
• Relationships: Relationships can as well be used for representing edges in the graph. They help in initiating relationships between nodes.
• Properties: The Properties represents the information associated with the nodes.

Graph Database Models

We have two common graph database models, these are;

• Resource Description Framework (RDF) graphs
• Property graphs

Resource Description Framework (RDF) graphs : These graphs concentrates on data integration. They consist of the RDF triple whereby each is recognized by a unique resource identifier. The RDF graphs are often used by agencies, healthcare companies, statistics etc.

Property graphs: Property graphs are much more illustrative, of which each of the elements carries properties and attributes that further determine its entities. This type of graph is very useful in data analysis.

Applications

Now, let’s talk about the applications of graph databases. Each are outlined below;

Social Media Platform: Graph database is very efficient for social media platform where it can store all users and analyze their engagement. This is very useful for analyzing different users behavior and distinguishing groups for marketing purposes.

Fraud Detection: Graph database is also an essential tool for fraud detection. It’s capable of tracking and mapping out most complex networks of relationships whereby running a simple query will help in identifying the fraud.

Now, let’s discuss the advantages and disadvantages of the Graph Database.

Advantages of Graph Database

• It is easier to spot trends and recognize elements with the most influence
• We don’t need a join when we have defined relationships
• It is flexible and agile
• Our Query usually depends on concrete relationships
• Graph Database is very good at establishing relationships with external sources

Disadvantages

• NoSQL databases are designed to work for a specific purpose .They are not a universal solution designed to replace all other databases.
• The Database are hard to be scaled across a number of servers.
• The query language is also platform dependent.
• In handling complex relationships, the speed becomes slower while searching.
• It also has a smaller user base.

Let’s move further by doing a comparison of NoSQL Graph Database with other relational databases.

NoSQL Graph Database Vs. Relational Database

Relational databases that is, MySQL and PostgreSQL, usually store data by using an explicit schema. On the other hand in a NoSQL database, users don’t define a schema. They would rather store the data using any structure they desire. We can say ‘SQL’ and ‘NoSQL’ actually refers to how our schemas are defined.

Another main differences between relational databases and NoSQL systems is that while relational databases broadly supports minimal transactions, NoSQL systems on the other hand allows transactions to run on any row.

The demand for graph database is actually realized by the level of connectivity between data. We can say graph database is a great choice for data analysis rather than simple data storage. Also, if we want to move with constantly changing data, a NoSQL graph database should be considered.

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