Graph Data Models 101
When building an app, you might wonder which database is the best choice. A traditional relational database that you can query using SQL is a familiar choice, but does a relational database really provide a natural fit to your data model, and the performance that you need if your app goes viral and needs to scale up rapidly?
This tutorial takes a deeper look at data modeling using relational databases compared to graph databases like Dgraph, to give you a better understanding of the advantages of using a graph database to power your app. If you aren’t familiar with graph data models or graph databases, this tutorial was written for you.
Learning Goals
In this tutorial, you will learn about graphs, and how a graph database is different from a database built on a relational data model. You will not find any code or syntax in this tutorial, but rather a comparison of graphs and relational data models. By the end of this tutorial, you will be able to answer the following questions:
- What is a graph?
- How are graphs different from relational models?
- How is data modeled in a graph?
- How is data queried from a graph?
Along the way, you might find that a graph is the right fit for the data model used by your app. Any data model that tracks lots of different relationships (or edges) between various data types is a good candidate for a graph model.
Whether this is the first time you are learning about graphs or looking to deepen your understanding of graphs with some concrete examples, this tutorial will help you along your journey.
If you are already familiar with graphs, you can jump right into our coding example for React.
If you are a SQL user and you’d like to learn how common SQL syntax maps to similar GraphQL syntax so you can use your SQL knowledge to jump-start your GraphQL learning journey, see Introduction to Dgraph for SQL Users.