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: A Feature Comparison

Aspect	GraphQL	REST
Definition	A query language for APIs that lets clients request exactly the data they need.	A standardized architecture for building web services that uses HTTP requests to access resources.
Example	A single query can fetch user data, posts, and comments in one request.	Multiple endpoints are needed to fetch user data, posts, and comments separately.
Companies Using It	Facebook, GitHub, Shopify, Twitter	Google, Amazon, Microsoft, Netflix
Benefits	Flexible data retrieval, reduced over-fetching, strong typing, and introspection.	Simplicity, standardization, caching support, and wide adoption.
Drawbacks	Complexity in setup, and potential over-fetching in complex queries, require a learning curve.	Multiple endpoints can lead to over-fetching, less flexible, versioning issues.
When to Use	Use when needing flexible queries, complex data relationships, or real-time updates.	Use for simpler applications, when caching is essential or for well-defined APIs.

GraphQL vs REST– What are the Differences ?

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

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.

GraphQL vs REST – Summary

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.

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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.

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. 

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