What are the GraphQL benefits over REST?
This article will explain the advantages of using GraphQL over REST. It provides an overview of GraphQL, the challenges of using REST for specific use cases, and how GraphQL solves these problems.
GraphQL was developed by Facebook and released as an Open Source application in 2012. It functions as a query language designed for APIs. In essence, client applications use it to load data from the server.
It has a reputation for being more efficient than traditional services. To be candid, GraphQL is unique; it is far more efficient than competing programs. That is why many organizations are adopting it for building APIs.
This article will compare and contrast both REST and GraphQL APIs. We will take a closer look at the drawbacks of REST and how GaphQL proffers a solution that enhances efficiency and productivity.
After that, we shall consider the multifaceted benefits that GraphQL offers developers. This article provides valuable information that lets you decide if you need to switch from REST to GaphQL.
- 1 What are the Challenges of the Current REST API?
- 2 Can GraphQL Make a Difference?
- 3 What are the GraphQL Benefits for the Developer?
- 4 What do I do next? Abandon REST for GraphQL?
- 5 Getting Started with GraphQL
- 6 GraphQL Learning Resources
- 7 In Conclusion
- 8 What are the downsides of the REST API?
- 9 What are the benefits of GraphQL?
What are the Challenges of the Current REST API?
Let’s consider this scenario to illustrate the prevailing challenge with the current REST API.
There is a need to fetch data using the Facebook REST API. You fired up your REST code requesting data from Facebook. However, in practical terms, your code is directed to a specific endpoint or URL.
After receiving the request, the URL or endpoint controls the data that is released to you. You can streamline and organize the data that is released back to you by adding certain options or parameters into the URL.
However, the current REST API has two main challenges which are described below:
- The first issue with REST Over Fetching. This refers to delivering that is more than what is requested. In essence, not all data delivered are useful for the purpose of your request.
- The second challenge is Under Fetching. This refers to drawing data that is not adequate for your purpose. This compels you to run the query all over again.
Most traditional REST APIs use endpoints in the following format /classmate or /myClassName:ID. In scenarios where the endpoint does not have an ID, all the data at that endpoint is delivered. But the queries that end with an ID delivers only the data related to the resource requested.
Consequently, the first scenarios deliver data that is far more than you need, while the second scenario (with an ID) delivers data from a precise ID in a specific endpoint. In essence, queries that do not go with an ID delivers huge data, most of which are not required.
The problem with over fetching cannot be apparent when you are running a small app with just a handful of classes and small userbase. However, when you start to scale, it becomes a major bottleneck. It takes a toll on app performance and data throughput.
Consequently, the cost of maintaining your backend begins to rack up as you transfer massive data. No thanks to the repeated queries from your REST API calls.
Can GraphQL Make a Difference?
Consider the illustration below. The comparison is an excellent example of the positive changes that GraphQL brings.
A traditional API is similar to going to a restaurant and requesting for a plate of food. After getting served, you simply eat what you want from the plate and leave the rest for the restaurant to discard.
On the other hand, GraphQL is like going out to eat in a self -service restaurant. You will likely choose a combination of things you love and in the right quantities. After your menu, there will be no leftovers, no wastages.
Now here is the real deal: GraphQL was created to make smart queries by requesting the exact data you need. This is in direct contrast to REST, where you are compelled to accept any data that is handed over to you. The result of using GraphQL for queries is listed below:
- Able to request all types of data.
- Can obtain cumulative data from multiple sources
- Can request selective and specific data from an API’s endpoint.
Let us take a look at the code on the official website of GraphQL
With the code below, we have defined the structure of our data. Let’s assume that this project requires specific data as follows: name, tagline, and some contributors.
This is the code that describes the data.
After defining the data structure, the next step is to request the data. Unlike REST, where you simply hit an API and accept the data that is delivered, you will be running a query instead. It is like requesting that the GaphQL project be opened and extract only the tagline from the project.
Make specific requests:
After running the query above, only the data that you requested will be fetched. When you use the query above, an object containing the project and tagline alone will be delivered rather than the project with all of its content.
The result is predictable:
What are the GraphQL Benefits for the Developer?
Below, you will see the GraphQL benefits over REST.
Benefit #1: GraphQL makes the life of frontend teams easier.
One of the most obvious benefits is that less code is required to perform frontend functions. Moreover, it is easier to understand because developers can analyze the object and know what to expect the API to return. This results in a faster project turnaround for both the frontend and backend teams.
At a glance, you will notice that the GraphQL queries replicates its response. As a result, you can predict the data that the query will return. Consequently, the developer can write queries easily. All that is required is to know the data that the app needs from the backend.
Benefit #2: Using GraphQL, API versioning is no longer a problem
Bear in mind that the client’s query goes a long way to determine the shape of data that is returned. This feature makes it easier and simpler to generalize servers. For instance, when you have new product features, you can easily add additional fields to the server and other clients will not be affected.
Another scenario is when the needs arise for sunsetting older features, you can simply deprecate the server fields, but also allow them to keep on working. With this gradual migration that uses backward compatibility functions, incremental versioning is no longer required.
Benefit #3: GraphQL is dynamic
One of the major benefits of GaphQL is the dynamism of the API, which allows you to define it quickly. Consequently, the frontend and backend teams can work more cordially with enhanced productivity. And the turnaround time for projects becomes faster.
The benefits list is vast is here is a couple more:
- Less data fetching –> Lower data transfer costs
- Less data fetching –> Faster application load times
- Less data fetching –> Makes your app work better with slow network connections
What do I do next? Abandon REST for GraphQL?
You do not have to abandon REST altogether.
There is no need to migrate applications that have been designed to use REST API. Rather, you should plan to use GaphQL for future applications. GraphQL can be a lifesaver when building scalable applications.
It is crucial to be mindful of the fact that GraphQL and REST are not the same. You can view REST API as an architecture pattern, while GraphQL is a technology and a language. In essence, the REST API is well established, and it is not going anywhere soon. GraphQL is a useful resource that makes you derive more value from REST.
For most applications, there won’t be any increase in performance by simply migrating to GraphQL. However, when an app starts to scale, that is when the value of migrating to GraphQL comes to play. It presents a powerful and elegant solution for teams that have been restricted to the traditional REST API.
Getting Started with GraphQL
GraphQL is highly dependent on the data requirements of developers, designers, and the products itself. This dependence on data makes it very easy to use by beginners and experts alike.
First of all, you will need a server in place which will host your API. After that, you will set up a client that will fetch the endpoints from the server. You can host the server by yourself using NodeJS, Express, and GraphQL. A better solution is to allow a professional service such as Back4App Serverless GraphQL API to take care of the backend hassles for you.
Once you have your backend in place, the next step is to simply create an app and start using it. You can check this easy to use guide for more information. There are various ways of getting the client up and running, we recommend that you try Facebook’s Relay and React if you want to explore new possibilities.
GraphQL Learning Resources
One vital learning Resource is the GraphQL API console at Back4pp. It presents the developer with an autocompletes feature, which suggests the possible steps in creating a GraphQL query or mutation. Moreover, the results of query and mutation are displayed in real-time, allowing you to see the response of your code immediately.
Besides all these useful features, you can access fully specified schemas for all your app classes. These schemas are available for download, so you can integrate them into your projects.
You can also access documentation for various generic and specific methods. The documentation can serve as references while performing your development tasks.
GraphQL is a new technology that offers developers the advantage of building scalable APIs that are not limited by the shortcomings of REST APIs. It allows developers to easily describe, define, and request specific data with an API.
Let us know what you think about GraphQL. Do you have any questions? You submit your questions in the comment section below. We will be glad to help.
What are the downsides of the REST API?
– Over fetching
– Under fetching
– Data transfer costs
What are the benefits of GraphQL?
– Solves over/under fetching problem
– It’s dynamic
– Reduces data transfer