Data Fetching: GraphQL vs REST

An Introduction to GraphQL & REST

When building an API, REST has known to be the standard for API creation. It offers a stateless server and boasts structured access to resources. However, REST APIs are also known to be inflexible when keeping up with rapidly evolving client requirements and in data fetching. 

Consequently, GraphQL an open-source query language was developed to address the need for increased flexibility and efficiency. It allows for declarative data fetching, enabling clients to specify the data required from the API, essentially future-proofing the platform.

This blog highlights the key differences between GraphQL and REST API, helping you make an educated decision on which solution best suits the unique requirements of your business. 

What is REST?

REST (Representational State Transfer) is an architectural standard that conforms to a set of guidelines and constraints when developing web APIs. As its name suggests, when clients request data the REST API server transfers the resources in a standardized representation, returning all information about the source and its overall state, which is then translated into an interpretable format.

For example, when managing a work-order system it is essential that you have real-time access to the status (Pending, In-progress, Complete) of each task and the employee allocated to manage it. In order to download this data using REST, you would need to hit multiple endpoints that return fixed data sets, from which you will need to extract the required information. This example depicts the most common limitation of REST:

  • Over fetching is when you get more information than required: when requesting information on the employee assigned to each task, all data related to the work order will be retrieved.
  • Under fetching on the other hand means it is difficult to extract the exact data required in a single attempt: when requesting information on employee allocation, two calls are made, the first is to obtain the task list and the second is to get data on employee assignment.

The data formats supported by REST API include JSON, YAML, and XML. When working with data, REST APIs use HTTP methods to describe the type of requests sent to the server, they are: GET, POST, PUT, and DELETE, these methods are used to effectively perform CRUD (Create, Read, Update and Delete) Operations. REST APIs also allow for modifications and add-ons from the client-side to the server.

What is GraphQL?

GraphQL is an open-source data query and manipulation language that can be used to work with APIs, enabling clients to make HTTP requests and benefit from a high runtime in fulfilling queries with existing data. GraphQL has a high adoption rate across varying verticals and use cases, it is used by teams of all sizes, from different environments and languages.

The information seen in GraphQL is in the context of a graph, with nodes used to depict objects. As opposed to making multiple requests to fetch data, GraphQL allows users to make ad hoc, tailored requests for data from various endpoints and resources with a single request. GraphQL’s declarative nature also empowers users with a predictable data structure that is highly efficient and readable, as users are able to specify and obtain the exact type of data required from the server without unwanted inclusions, ultimately preventing the over-fetching and under-fetching of data.

GraphQL vs REST API: Which is Better?

The answer to this question is subjective and depends heavily on project requirements and their related attributes: application architecture, user base, data load in the front end, and performance objectives.

For instance, if you are looking to integrate a new application or process into your API development using a modern, interactive interface and design style that is not subjected to multiple round trips when fetching specific data, GraphQL is likely to be the ideal platform. Its query language and set of tools that operate over a single endpoint enable a declarative and flexible nature that provides for a smooth and fast development environment.

However, if you are seeking out an "architectural concept" for network-based software and a proven technique that offers resilient native authentication or caching, REST might be your best bet. REST APIs can be developed to meet a user-specific need, it is also very easy to build and adapt, enabling easy development across various projects with greater software scalability. 

Conclusion

It is highly recommended that you conduct a study on the needs of all participants in the API value chain when building an API product that is designed to optimize processes and streamline operations. When choosing your API design style, it is important to be aware of all associated tradeoffs and constraints in order to pick the option that best suits the requirements of the API Consumer (Developer), API Provider, and the End-user (Customer). You could even consider deploying a mix-and-match approach that uses both REST and GraphQL to effectively manage the data fetching requisites of the API.


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