Multinational companies often struggle with managing and organizing loads of data. That’s where graph technology offers them respite.
You can use a graph database to represent complex, interconnected data in a simpler manner. Using graphs helps with a better user interface and an easy data retrieval process.
What are Graphs?
Graphs are widely used in mathematical calculations. It consists of a set of objects, also known as vertices, that are interconnected by lines called edges.
Graphs are an easy-to-understand and time-saving method of handling information. They can help you understand the flow of information between databases. Graphs are of different types like:
- Directed or undirected Graphs
- Line Graphs
- Bar Graphs
- Combo Chart
- Pie Graph
What is a Graph Database?
According to recent reports, the global graph database market is expected to reach US $4,603.4 million by 2027.
A graph database is a specialized form of the database engine that can create and manage graphs. It can help store and manage inter-related data and map them accordingly.
The database is a better choice than relational and hierarchical databases. A relational database uses a tabular form with rows and columns to store data.
How does a Graph Database Work?
A graph database is a powerful tool to link diverse information. It uses different graph models to manage real-world data. The vertices of the graphs represent an entity like a person, place, or object. The edges stand for the relationship between those entities.
An edge has a start node, end node, and direction. It represents the flow and connectivity of information between the entities. Hence, graph databases focus on the relationship between the entities more.
You can access, modify, and traverse through the graphs using various algorithms. Graph algorithms play a vital role in the field of computer science and programming.
Uses of a Graph Algorithm
A graph algorithm can identify the connections between the vertices and analyze the data in graphs. You can use semantic searches in your data query. It is an organic way to retrieve using exact keywords and gives relevant results.
Social media accounts use graphs to store details about users. For example, in a social media account, a graph algorithm can identify the relationships between users like friends or friends of friends.
A sorting graph algorithm can help to handle queries and provide efficient data search techniques. Depth-first and breadth-first search are the most common algorithms used to search data in a graph database.
A depth first-search searches the next node below the entity, while a breadth-first search moves from vertices on the same level.
Some other kinds of algorithms that are used in a graph database are:
- Shortest path
- Cycle detection
- Minimum spanning tree
- Strongly connected components
- Graph Coloring
Data stored in a graphical format provides a flexible platform to analyze and manage interconnection information.
Graph databases can be used to explore complex data used in banks, hospitals, educational institutes, and many social media networks.
Retail businesses can use graphs to store client data for efficient customer relationship management.
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