---
title: "What are the advantages of using a graph-based NoSQL database?"  
description: "What are the advantages of using a graph-based NoSQL database?"  
author: "Utpal Vishwas"  
published: 2023-04-25  
updated: 2023-04-26  
canonical: https://www.mindstick.com/forum/158012/what-are-the-advantages-of-using-a-graph-based-nosql-database  
category: "database"  
tags: ["database", "nosql"]  
reading_time: 3 minutes  

---

# What are the advantages of using a graph-based NoSQL database?

What are the [advantages](https://www.mindstick.com/articles/12841/5-advantages-of-customer-portal-you-didn-t-know-about) of using a graph-based [NoSQL database](https://www.mindstick.com/forum/160347/how-do-you-retrieve-data-from-a-nosql-database-like-mongodb)?

## Replies

### Reply by Krishnapriya Rajeev

A graph database is a type of NoSQL database system that uses a *topographical network structure*. The concept for such a database system arises from mathematical graph theory, which uses nodes, edges, and characteristics in graphs to describe data sets.

While relational databases were (and still are) the industry standard, it is only in recent years that graph databases have shown to have major advantages over relational databases due to a need for more sophisticated data activation requirements, real-time query response times, frequent schema modifications, as well as to manage exponential data volumes.

A few of these advantages from a data management point of view are as follows:

1. Graph databases are designed to store and manage complex relationships between data points. They can efficiently model and query data relationships between different entities, such as people, products, and locations.
2. In order to navigate the network and retrieve data, graph databases use graph theory algorithms. They may therefore quickly extract data using intricate graph queries that would be difficult or impossible to execute against other types of databases.
3. The flexible schema architecture that graph databases provide makes it simple to add new nodes and relationships to the graph. Because of this, you may continue to develop your data model over time without having to worry about schema migrations.
4. Graph databases can be easily scaled horizontally to handle large datasets and high query volumes. This is because they store data across multiple nodes and can distribute queries across multiple servers.

### Reply by Aryan Kumar

Graph-based [NoSQL](https://www.mindstick.com/articles/12053/big-data-nosql-data-stores) databases are designed to store and manage graph data, which is data that represents complex relationships between entities. Graph databases are optimized for fast traversal of these relationships, making them ideal for use cases such as social networking, recommendation engines, fraud detection, and network analysis.

Some advantages of using a graph-based NoSQL [database](https://www.mindstick.com/articles/12226/use-of-database-in-sencha-extjs-and-insert-record-from-user-form-using-ajax) include:

1. **Flexibility:** Graph databases are highly flexible and can handle complex and dynamic data structures, making them ideal for use cases where the data model is constantly changing.
2. **Performance:** Graph databases are optimized for fast traversal of relationships between entities. This makes them ideal for use cases where you need to perform complex queries or traverse large amounts of data quickly.
3. **Scalability:** Graph databases can scale horizontally to handle large amounts of data and high traffic loads. This makes them ideal for use cases where you need to store and process large amounts of data.
4. **Data Integrity:** Graph databases maintain data integrity by enforcing relationships between entities. This makes it easy to ensure that data is consistent and up-to-date.
5. **Natural Representation of Data:** Graph databases offer a natural way to represent and store data. This makes it easy to visualize the data and understand the relationships between entities.
6. **Easy to Query:** Graph databases offer a declarative query language that makes it easy to query complex relationships between entities. This can save time and effort in developing complex queries.

Some examples of graph-based NoSQL databases include Neo4j, OrientDB, and ArangoDB.


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