Are you struggling to manage your growing amount of data? Are you frustrated with the limitations of traditional relational databases? It may be time to start using a graph database.
So, what is a graph database? The following article will explain graph databases and their common uses.
Understanding Graph Databases
According to reports, the global graph database market is valued to reach $5.2 billion in the year 2026.
Graph databases usually store data as nodes and relationships. It means they are made up of entities (nodes) with properties (attributes), and those entities connect with relationship types.
The relationship type can be defined as an edge in a graph database.
Nodes and edges are very similar to records in a relational database schema. The critical difference is that nodes and edges have properties attached to them.
Graph databases are a type of NoSQL database that derive from a non-relational model, which means they can be technologically classified as a modern data structure.
Common Uses of Graph Databases
Now that you know what is a graph database, here are some commonly used examples include:
1) Fraud Detection
Fraud detection is an example of a use for a graph database. According to industry experts, fraud detection is one of the most common uses for graph databases.
Fraud exists in many forms – from an individual using a fake identity to purchase products, purchasing items without paying your entire balance, or individuals committing healthcare fraud by filing false claims. Fraudulent activities are performed by criminals looking for ways to exploit and manipulate data to their advantage.
Companies can use graph databases to prevent criminals from exploiting data while at the same time continuing to provide a high-quality consumer experience.
2) Customer Relationship Management (CRM)
Customer relationship management is another widespread use of graph databases. CRM software allows companies to track and analyze consumer records and interactions.
Graph databases can be used to manage a company’s data related to customers, including contact history, customer service communications, and transactions between a company and a customer. Through a graph database, companies can track consumer contacts over time – from the moment of first contact through any potential follow-up or responses.
Companies can use the data to identify and fix potential problems while also developing and maintaining strong consumer relationships.
3) Social Media Analysis
Graph databases can be used for social media analysis. Graph databases allow companies to connect with consumers on a more personal level by identifying key influencers.
For example, a company may sell shoes and target famous athletes and celebrities with large social media followers as key influencers. The company would use a graph database to identify these individuals and make them aware of users’ products. Then, the company can track the performance of these offers by monitoring product sales and analyzing follower engagement.
4) Logistics Management
Another everyday use for a graph database is logistics management. Managing supply chains can be complicated, primarily when multiple companies work together.
For example, a company may have to manage products sent from one warehouse to another. A graph database can be used to easily track products throughout their supply chain, including tracking product movement and consumer information.
Companies can use the data in this way to make sure products are being delivered on time and that any issues or delays are quickly identified and resolved.