GraphQL vs REST – 10 Top Key Differences (Testers Edition)

Now, as we go into the vast subjects of APIs, there are various approaches and architectural patterns. Over the years, there has been multiple approaches which follow different architectural patterns that provides different standards to build APIs but the most predominant patterns that are used in the recent times are REST and GraphQL.

GraphQL vs REST – Overview

GraphQL:

• First, let’s look into GraphQL. This is basically a query language for the APIs.
• It also functions as a server-side runtime for executing these queries.
• By using GraphQL, The Clients can request for the data that they exactly need from the service. 
• Testing GraphQL is also effortless with open-source APIs. 
• In GraphQL the clients will have to explicitly define a schema as it specifies the fields that need to be queried which helps in structuring the responses based on the requirements. 
• This helps avoid unnecessary data fetching or missing crucial information.
• GraphQL simplifies communication between systems by allowing precise data requests, adapting to changing requirements, and remaining independent of the underlying database.
• In GraphQL, we define the Queries for performing GET requests and Mutations for the remaining part of CRUD operations that include Create, Update and Delete.

REST

• REST, also known as Representational State Transfer, is an architectural style defining rules for creating web services.
• The RESTful web services work with the HyperText Transfer Protocol.
• It exposes endpoints defined with these standards and uses standard http status codes such as 200, 404 , 500 for communication . 
• They utilize HTTP methods like GET, POST, PUT, PATCH, and DELETE for CRUD operations.
• In RESTful services, the client sends requests using HTTP methods (GET, POST, etc.).
• The server responds with a resource, which can be HTML, XML, Image, JSON, etc.

GraphQL Vs REST: An Example

Let’s understand the difference between GraphQL vs REST with an example. Consider you have an API that retrieves a user’s name and address. The request/response in a REST scenario will look like this,

In REST, the resources are identified by the request type (GET, POST, etc) and the URLs. But, if the API server is GraphQL, then the API calls will look like this,

The JSON response varies with different queries sent by the client, as shown below,

You wonder why? Let me simplify this for you. Unlike REST API, where you make two API calls to retrieve data, GraphQL makes one API call to retrieve the same data. That is, GraphQL simplifies the process by making ad-hoc queries to a single URL endpoint to fetch data.

GraphQL vs REST – Which Companies Use?

Some of the companies that use GraphQL on their servers are as follows:

• Facebook, the brains behind GraphQL, has been using it since its development.
• GitHub GraphQL API allows users to create integrations, automate workflows, and retrieve data.
• Other popular companies that use GraphQL include Pinterest, Coursera, Shopify, Intuit, etc.
• On the other hand, REST API is also used by top companies like YouTube, Google, X (formerly Twitter), LinkedIn, etc.

GraphQL vs REST – Drawbacks and Benefits

Let’s take a quick peek at the advantages and disadvantages of GraphQL vs REST API.

Drawbacks of REST

• REST API exhibits less data control, resulting in over-fetching and under-fetching of data. Consequently, multiple endpoints need to be exposed to access different resources. 
• Clients may need to access multiple endpoints at times to get the desired information, thereby leading to performance and optimization issues. Additionally, real-time updates pose challenges in REST, lacking an inherent mechanism like GraphQL’s subscription. 
• To achieve real-time updates, clients must resort to mechanisms such as polling or web sockets, maintaining an open connection rather than terminating it.

Drawbacks of GraphQL

• GraphQL introduces a steeper learning curve due to the necessity of explicitly defining a schema. 
• The schema definition process requires careful consideration, as additional fields may contribute to over-fetching, and omitting required fields can result in under-fetching. 
• Moreover, GraphQL queries may encounter the N+1 problem, particularly in scenarios with intricate nested data model relationships. 
• The N+1 problem is a performance challenge arising when querying complex nested data, especially across multiple databases in a single query. This complexity can impact the efficiency of response times, particularly when dealing with extensive datasets. 
• Efficient schema design, consideration of data requirements, and addressing the N+1 issue are essential aspects of optimizing GraphQL implementations.

Benefits of REST

Though GraphQL is becoming increasingly popular, REST is still one of the most widely used API standards. Let’s understand why.

• Learning Curve: REST API is simple and easy to learn, which is the biggest advantage when compared to other APIs.
• Complex Request: In REST, each request has its own endpoint, making complex requests easier to manage compared to other APIs.
• Clean and Simple: It is straightforward and easy to navigate.
• Standard HTTP Procedures: It utilizes standard HTTP procedures for data retrieval and requests.
• Serialization: It offers flexible methods for serializing data in JSON.
• Client/Server: Business logic in REST is separate from presentation, allowing changes in one without affecting the other.
• Caching: REST APIs can handle heavy traffic efficiently using an HTTP proxy server and cache.
• REST Is Stateless: All messages between client and server contain enough context for processing, ensuring efficient communication.

Benefits of GraphQL

GraphQL offers several benefits over other APIs, making it increasingly popular for building modern web and mobile applications. Some of the key benefits of GraphQL include:

• Single Request, Multiple Resources: With GraphQL, clients can combine multiple queries into a single request. This speeds up processing, decreases wait times, and minimizes network traffic.
• Efficient Data Retrieval: GraphQL enables clients to request only the necessary data, avoiding unnecessary data retrieval. This streamlines the process and reduces the amount of data sent over the network.
• Flexible Schema and Strong Typing: GraphQL offers a flexible schema that clients can use to specify their data needs. It also enforces strong data typing, ensuring clarity in communication between the client and the server.
• Developing APIs without Versioning: GraphQL allows APIs to evolve smoothly by enabling the addition of new fields or types without breaking existing clients. This avoids the hassle of versioning and ensures a seamless transition.
• Real-time Data: It supports real-time data updates through subscriptions, which is particularly useful for applications like chat or collaborative tools requiring immediate data updates.

Why GraphQL is Faster than REST API

GraphQL is much more efficient than REST API. A quick look at some of the reasons that make GraphQL highly efficient than REST is as follows, 

• Reduced over-fetching
• Eliminates under-fetching
• Batched Requests
• Reduced round trips
• Efficient caching

When to Use GraphQL vs REST?

This is a crucial question that has to be addressed by the development and testing team. The choice between GraphQL vs REST depends primarily on factors such as the: 

• Project Data Requirements 
• Data Retrieval 
• Real-time updates
• Use Cases 
• Data Control 
• Schema and Flexibility 
• Speed and maintenance 

Before jumping into the analysis here is a quick overview: 

Why Use GraphQL Instead of REST?

• GraphQL is the preferred choice when dealing with complex data relationships, as it enables clients to efficiently retrieve nested data in a single query, thereby minimizing the need for multiple network requests.
• Its explicit schema definition allows for precise interactions with the data, mitigating issues such as over fetching and under fetching.
• Real-time updates occur when server data changes, and the client promptly accesses and responds to these changes. 
• GraphQL facilitates this through its Subscription mechanism, allowing clients to effortlessly respond to data updates.

Why REST instead of GraphQL?

REST is favored for straightforward data and frequent requests, benefiting for caching mechanisms due to its resource-centric architecture, where each endpoint represents a resource.

With REST, the response remains consistent across similar requests, making it efficient for caching scenarios where specific data is accessed frequently.

Real-time updates occur when server data changes, and the client promptly accesses and responds to these changes. 

REST requires the use of web sockets or polling for real-time updates, where the client keeps an open request to monitor data changes, as the standard request-response model would terminate the connection.

Now let’s take a look at some interesting points to sum up: 

Project Data Requirements:

GraphQL: It is preferred when there are requirements for dealing with complex data relationships.

REST: It is preferred for more straightforward data requirements and in cases of frequent requests.

Data Retrieval Efficiency:

GraphQL: This will efficiently retrieve the nested data in a single query, so it minimizes network requests.

REST: In case of REST, it benefits from caching mechanisms and provides consistent responses for similar requests.

Real-time Updates:

GraphQL: It uses a Subscription mechanism for real-time updates, this allows the clients to respond to data changes with minimal efforts. 

REST: It Requires a  web sockets or polling for real-time updates. This is due to the standard request-response model.

Use Cases:

GraphQL: This is suitable for fine-grained control, nested data scenarios, limiting bandwidth usage, and working with multiple APIs or sources.

REST: Whereas this is ideal for simpler applications, large data, web caching, and error monitoring.

Data Control:

GraphQL: It allows precise data requests in a single query and avoids over-fetching of data.

REST: In certain cases it may require querying multiple endpoints, and may lead to potential over-fetching of data. 

Schema and Flexibility:

GraphQL: This is built on a schema so it makes it easier to evolve APIs over time.

REST: It is a well-defined structure but lacks the flexibility of GraphQL’s querying mechanism.

Speed and Maintainability:

GraphQL: It can improve application speed by allowing clients to request only necessary data, reducing coupling.

REST: Although it is widely used it may face challenges with changing client requirements.

These are some important things to keep in mind when making a decision, REST can be suitable for simpler use cases, large data scenarios, and widespread use whereas graphql can be a good choice to opt for when precise control over data retrieval, avoidance of over-fetching, and adaptability are crucial. Although each has its own pros and cons, always consider project-specific requirements when making a decision.

How to Use Both GraphQL and REST Over the Same API?

• REST represents an architectural paradigm extensively used in crafting networked applications, relying on a stateless client-server communication protocol making use of standard HTTP methods such as GET, POST, PUT, and DELETE to execute api calls .
• In contrast, GraphQL serves as a query language for APIs and a runtime for executing these queries on data. Unlike REST, where fixed endpoints are exposed for each service, GraphQL offers a unified endpoint, allowing clients to precisely query the data they need. 
• This not only enhances flexibility but also reduces data transfer over the network. While both approaches have their merits and drawbacks, the adoption of both GraphQL and REST within the same API, termed a hybrid approach, proves practical and advantageous in specific scenarios. 

Here are some key differences that helps us to identify when and where to use GraphQL and rest over the same api

Data structure :

• Consider an application, such as a blog website, that encompasses various types of information. In the user profile section, where straightforward data like the user’s name, designation, and additional personal details are presented, a RESTful approach utilizing an endpoint like GET(user/${userID}) proves effective. 
• This endpoint, distinguished by a unique userID for each user, enables clients to retrieve comprehensive user information, including the name, designation, profile photo, and additional details.

• Shifting focus to another section of the website, like the blog section, where users can create posts with associated comments and likes, introduces a more intricate data structure. 
• A post includes details such as text content, an author, and a timestamp. Moreover, comments and likes are intricately related to posts, with each comment having specific details like the commenter’s name and the comment text. 
• Given this complexity, GraphQL emerges as an apt solution for efficient data management and retrieval. It allows clients to precisely request the information they need in a single query, ensuring a streamlined and flexible approach, especially advantageous in scenarios involving complex data relationships.

Existing project structure has rest implementation:

• If your project already follows REST principles, which involves exposing specific endpoints to perform operations on resources, it works well for straightforward data structures. For instance, fetching user details in the user profile section can be achieved through an endpoint like /user/{userId}, providing the necessary user information.
• However, when dealing with more intricate data structures, such as those found in a blog section, REST may encounter challenges. To retrieve data with nested relationships, multiple endpoints must be exposed, potentially leading to inefficiencies and data-related issues.
  
  Sample JSON

<styled-code>
{
  "posts": [
    {
      "id": "101",
      "userId": "1",
      "content": "An excellent post",
      "comments": [
        {
          "id": "1001",
          "text": "Awesome post"
        }
      ],
      "likes": [
        {
          "id": "10001"
        }
      ]
    }
  ]
}
</styled-code>

In REST, various endpoints like /users, /posts, /comments, and /likes are required to fetch the different resources. For example ,we will have to expose these number of endpoint to meet the client requirements

RESTful Endpoints to be created:

• /users: Get all users.
• /users/{userId}: Get a specific user.
• /posts: Get all posts.
• /posts/{postId}: Get a specific post.
• /comments: Get all comments.
• /comments/{commentId}: Get a specific comment.
• /likes: Get all likes.
• /likes/{likeId}: Get a specific like.
  

Whereas ,with GraphQL, a single query is crafted to retrieve all the necessary information about posts, their comments, and likes. The query specifies the fields of interest, allowing for a more fine-grained and efficient data retrieval process. We can define a Post type with fields such as id, userId, content, comments, and likes, capturing the complexity of blog post-related data

Example :

Schema :

type Post {

  id: ID

  userId: ID

  content: String

  comments: [Comment]

  likes: [Like]

}

Schema explanation

Post represents a blog post in our system . It has several fields like below .
id: A unique identifier for the post.

userId: It refers to the ID of the specific user who created the particular  post.

content: The text content of the post.

comments: They are an array of comments associated with the respective post.

likes: An array of likes associated with the post.

Query :

<styled-code>
query {
  posts {
    id
    content
    comments {
      id
      text
    }
    likes {
      id
    }
  }
}

</styled-code>

Query explanation

query is a GraphQL keyword indicating that we want to retrieve data.

posts is the name of the query, which fetches information about posts. Inside posts, we specify the fields we want for each post:

id: The unique identifier of the post.

content: The text content of the post.

comments:  They are an array of comments associated with the respective post.

id: The unique identifier of each comment.

text: The text content of each comment.

likes: An array of likes associated with the post.

id: The unique identifier of each like.

Returned response structure

The resulting JSON data reflects this structure, providing the requested details for each post, its comments, and likes.

<styled-code>
{
  "posts": [
    {
      "id": "101",
      "userId": "1",
      "content": "An excellent post",
      "comments": [
        {
          "id": "1001",
          "text": "Awesome post"
        }
      ],
      "likes": [
        {
          "id": "10001"
        }
      ]
    }
  ]
}
</styled-code>

In summary , GraphQL is a unified and flexible query that simplifies the process of fetching complex data structures, eliminating the need for numerous endpoints. The response structure is organized and tailored to the client’s requirements, promoting efficiency in data retrieval and reducing issues related to over fetching or under fetching. This approach is particularly advantageous when dealing with intricate data relationships, as seen in the blog section example and REST is more suitable for fetching straightforward data like seen in the user profile section example.

What are the Similarities Between GraphQL and REST?

GraphQL and REST are both technologies employed for crafting and developing APIs (Application Programming Interfaces), with distinct approaches. While these two API design methodologies diverge in their implementation, they do share certain commonalities. Despite the differences in their underlying architectures, these technologies exhibit some similarities that underscore their role in shaping the API landscape.

Communication protocol 

• Both GraphQL and REST utilize standard HTTP methods like GET, POST, PUT, and DELETE to perform operations on resources. 
• This shared practice provides developers with a familiar and compatible environment, particularly for those accustomed to working with APIs based on the HTTP protocol.

Authentication and authorization:

• Authentication is the process of verifying the identity of someone or something trying to connect to an API. It’s like showing an ID card to prove you are who you say you are. Both GraphQL and REST use familiar methods, such as API keys (like a secret password), OAuth (a way to log in using another service, like Google), or JSON Web Tokens (JWT, a secure way of proving you’re authenticated).
• Authorization is about what that person or system is allowed to do once authenticated. It’s like saying, “Alright, you’re allowed in, however you can only go to certain rooms or only see certain information as permitted.” These security measures, whether using GraphQL or REST, help keep data safe and only accessible to those who have the right permissions.

Statelessness:

• Both GraphQL and REST share the idea of being stateless, which means that each time a user’s device (like a phone or computer) talks to a server, it provides all the information the server needs in that one conversation. 
• This helps keep things simple and scalable when different devices are talking to each other. It’s like having a complete and self-contained chat between the user’s device and the server, making communication efficient.

Data format 

• Both REST and GraphQL use similar data formats to interact with APIs. In APIs, data formats define how information is communicated between the client (which can be a browser or application, often referred to as the frontend in terms of the tech stack) and the server (the service handling those requests, also known as the backend in terms of the tech stack). 
• Both REST (Representational State Transfer) and GraphQL employ JSON (JavaScript Object Notation) as their primary data exchange format.
  JSON, being the most widely recognized data exchange format understood by all languages, platforms, and systems, is the preferred choice. The server sends back data to the client in JSON format. Although less common, other data formats like XML and HTML are also supported.

Caching:

• Both REST and GraphQL endorse caching, allowing clients and servers to store regularly accessed data. This caching mechanism enhances the speed of communication between them. 
• In REST, servers use HTTP headers like Cache-Control and ETag to instruct clients on caching behavior. In GraphQL, clients often manage caching, automatically storing and reusing data for similar requests, providing more control over what data is cached.

What REST Limitations Does GraphQL Attempt to Overcome?

Data structure 

• In REST, when you request information about a resource using an endpoint, you get the same set of data every time. However, with GraphQL, you can tailor your request to ask for only the specific data you need. 
• This flexibility allows you to modify the structure of your data queries based on the requirements of your application. In contrast, with REST, each endpoint you access always provides the same fixed set of data.

Over-fetching and under-fetching of data 

• In REST, when you use an endpoint to get data, you always receive the same amount of information, and it leads to over-fetching (receiving more data than actually required) and underfetching (receiving less data than actually required ) and it’s often that client receives more data than needed.
• However, with GraphQL, you can precisely specify the data you want by defining the structure of your request in a single query. This ability helps you avoid getting too much or too little data, making the process of fetching information more efficient.

Multiple Requests for Related Data: 

• Rest requires exposing multiple endpoints for fetching the required data whereas with GraphQL, we can retrieve all the needed information in one go by making a single, well-structured query. 
•  In REST, to gather information for a scenario like a blog section mentioned earlier , we typically need to create separate endpoints like /users, /posts, /comments, and /likes, each returning specific data. However, with GraphQL, you can consolidate all these requests into a single query by defining a structured schema.
• This means you can request user details, posts, comments, and likes together in one go, simplifying the data retrieval process compared to REST’s need for multiple endpoints.

Versioning : 

• API versioning means creating different versions of an API to meet the needs of various clients and use cases.  Implementing a versioning strategy enables clients to persistently utilize the current version of the REST API while having the flexibility to switch or transition  to a newer version when ready. 
• In REST, versioning is commonly denoted by notations like “v1” and “v2” in API endpoints, representing different versions of the API. In GraphQL, versioning involves adjusting the data structure by redefining the schema over time to ensure existing applications can adapt without breaking.

What is the Difference Between GraphQL and REST?

Here is a table to explain the differences between GraphQL vs REST

Title	Rest	GraphQL
Definition	Rest, also known as Representational State Transfer, helps us in building APIs by following an architectural pattern with a defined set of http standards like GET, POST, PUT, DELETE for performing CRUD operations	GraphQL is a query language for APIs that aids in interacting with the data we need from a service. Clients can request what data they exactly need from the service thereby avoiding over fetching and under fetching of data
Data control	Each endpoint exposed return only the same set of response every time as a result of which over fetching or under fetching of data occurs	Each query is flexible and can be tailored according to the client requirements hence only the required data is extracted . GraphQL has more control over data compared to REST.
Data structure	The structure of the data or response to be returned from the server to the client is decided by the server, as each endpoint returns only a specific response.	Clients specify the structure of the response they want by defining a query, and the server returns data according to the requested schema.Clients have more control over the shape and content of the response in GraphQL compared to REST.
Number of request	Fetching complex data in REST often involves making multiple requests to different endpoints, contributing to a potentially higher number of requests. This is because REST relies on exposing multiple endpoints, each serving specific resources.	GraphQL excels in handling complex data structures by enabling clients to retrieve all necessary information with a single query. The flexibility of GraphQL lies in its schema definition, providing a more efficient and tailored approach compared to REST.
Real time updates	REST requires the use of web sockets or polling for real-time updates, where the client keeps an open request to monitor data changes, as the standard request-response model would terminate the connection.	GraphQL facilitates this through its Subscription mechanism, allowing clients to effortlessly respond to data updates
Caching	Caching is more straightforward in REST since it relies on fixed endpoints that returns the same response structure	Caching is more challenging in GraphQL since there is no fixed response structure. The dynamic nature of GraphQL queries, where clients can request various fields and relationships, makes it less predictable for caching mechanisms.
Error handling	REST relies on standard HTTP status codes (e.g.200 for success, 400 for client errors, 404 for not found, and 500 for server errors) to convey the result of the network request.	GraphQL always returns a status code of 200 regardless of the success or failure of the request. However, in case of errors it includes an “errors” field in the response body to convey any errors encountered during the execution of the query
Versioning	In REST, versioning is commonly denoted by notations like “v1” and “v2” in API endpoints, representing different versions of the AP	In GraphQL, versioning involves adjusting the data structure by redefining the schema over time to ensure existing applications can adapt without breaking.
Schema	The structure of data to be returned from the server to the client is determined by the server hence there is no explicit schema defined in REST hence resulting in over fetching and under fetching of data	The structure of data to be returned from the server to the client is determined by the client by explicitly defining a schema thereby providing more data control when compared to REST
Learning Curve	Simpler to learn and understand due to its straightforward principles but handling complex data structures might require multiple endpoints	The learning curve can be a little steeper when compared to REST since it requires defining schema but it provides more flexibility in data retrieval and offers greater complexity while handling complex data structures

Key Differences: GraphQL vs REST?

GraphQL and REST are two most predominantly used approaches when building APIs . Here are some key differences between them in terms of – data fetching , defining schema , real time updates , versioning and caching. 

While we’ve touched on certain aspects in the “When to use GraphQL vs REST?” discussion, let’s now explore some key differences in greater detail.

Data fetching : 

In rest , data is fetched from the server by exposing endpoints , when you use an endpoint to get data, you always receive the same amount of information, and it leads to over-fetching (receiving more data than actually required) and underfetching (receiving less data than actually required whereas in GraphQL clients can request what data they exactly need from the service by defining a schema thereby avoiding over fetching and under fetching of data.

Defining schema:

In REST, each endpoint exposed always returns the same data and the structure of data to be returned from the server to the client is determined by the server and hence there is no purpose of schema to defined explicitly whereas in GraphQL , defining a schema explicitly on the client side plays a vital role since it allows to create flexible queries thereby defining what data needs to returned from the server

Real-time updates :

Real-time updates occur when server data changes, and the client promptly accesses and responds to these changes. GraphQL facilitates this through its Subscription mechanism, allowing clients to effortlessly respond to data updates whereas REST requires the use of web sockets or polling for real-time updates, where the client keeps an open request to monitor data changes, as the standard request-response model would terminate the connection.

Error handling : 

Rest makes use of standard http methods for communication hence in case of errors it makes use of standard http status codes like 200 , 400, 404 and 500 for determining the status of request . For example, for a successful response it returns a status code of 200 and in case of server side errors it returns a status code of 500 whereas, in GraphQL irrespective of the status of the request be it successful or unsuccessful it always returns a status code of 200 . However , In case of errors it includes an error field along with the details of the error in the response 

GraphQL vs REST: Which is Better?

• Choosing between GraphQL and REST depends on the nature of your project. If your data neatly fits into a resource-centric model, where each endpoint represents a distinct resource, REST might be your go-to.
•  On the flip side, if your data involves intricate relationships and you want to fetch nested information efficiently in one go, GraphQL could be your superhero.
• Remember, it’s all about the specifics of the project. Each—GraphQL and REST—comes with its perks and challenges.
•  Consider your data model intricacies, how you want to handle caching, and the level of flexibility you need in retrieving data. 
• Based on these details then tailor your choice based on what suits your project’s unique needs.

Automate your end-to-end UI tests for web, mobile, desktop applications and APIs, 5x faster, with Testsigma

Role of Testsigma with GraphQL and REST

Testsigma is a unified low-code cloud-based AI-driven test automation tool that supports automated web, mobile, desktop app, and API testing in one place. Testsigma specializes in automated API testing by offering capabilities for both REST and GraphQL API testing. Let’s take a quick look at it:

GraphQL Testing: With Testsigma, you can create test cases to interact with GraphQL APIs. It provides features to send GraphQL queries and validate the responses against expected results.

(Automated REST and GraphQL API testing using Testsigma)

REST API Testing: Similarly, Testsigma supports testing REST APIs. You can create test cases to send HTTP requests (GET, POST, PUT, PATCH, DELETE) to REST endpoints and validate the responses returned by the API.

Conclusion :

In conclusion, GraphQL and RESTful APIs function as potent instruments for crafting and deploying web services, each carrying out its distinct advantages and considerations. REST, valued for its simplicity and widespread acceptance, stands as an optimal solution for uncomplicated and stateless applications. Conversely, GraphQL shines in situations prioritizing flexibility and efficiency in data retrieval, presenting a customized approach to address intricate data demands. Ultimately, choosing between GraphQL and REST boils down to the project’s unique requirements and developers can consider factors like simplicity, performance, and data interactions to decide on the most fitting API architecture.

Frequently Asked Questions

Is GraphQL or Rest – still relevant?

• GraphQL is being widely adopted and used in the web development community . Its popularity is increasing because of the various advantages it imposes such as handling complex nested data model relationships , real time updates and increased data control thereby avoiding over fetching and under fetching of data . 
• Many organizations have adopted GraphQL because of the challenges posed by REST such as handling complex nested data models as a result Developers and organizations are likely to find GraphQL a valuable tool for addressing the complexities of data retrieval in modern applications.