GraphQL – 3 ways you use it without even knowing you do

In the chaotic universe of web development, where APIs battle against under-fetching villains and over-fetching monsters, a superhero emerged from the depths of Meta’s coding lair in 2012. With its cape of flexibility, powers of efficiency, and the ability to empower clients, GraphQL has become the caped crusader of the digital world. 

In this article, we are diving headfirst into the world of GraphQL to understand its essence and how it differs from traditional REST APIs. From social media behemoths to e-commerce giants, we will also explore 3 examples of its use in widely popular real-world applications. So, let’s get cracking!

What is GraphQL – Understanding the concept

GraphQL is a query language for reading and mutating data in APIs (Application Programming Interfaces). Developed in 2012 by Meta and released as an open-source project in 2015, GraphQL has garnered significant popularity amongst developers for its efficiency and flexibility. At the heart of GraphQL is the schema, which defines the relationships and types in the data model. It serves as a contract between the client and the server, specifying the types of data that can be queried and the structure of the responses. GraphQL comes with its own query language that enables clients to request only the data they require. This reduces under-fetching and over-fetching. 

GraphQL queries have a hierarchical structure that mirrors the shape of the data they request, thus making it easier to understand and organize complex queries. In GraphQL APIs, the types of data and the relationships between them are explicitly defined, helping in early detection of errors in development. In addition to queries, GraphQL also supports mutations which are used to modify data on the server. This enables clients to make changes to the data, such as creating, updating, or deleting records. 

REST vs GraphQL – Clash of the bigwigs

GraphQL and traditional REST (Representational State Transfer) APIs are both technologies used to build and consume APIs. In practice, both of these technologies send HTTP requests and receive HTTP responses. But they have distinct differences in their approach to data retrieval and manipulation. 

Data retrieval:

With a REST API, you fetch a URL and the URL returns a JSON or a JavaScript object full of data. The server predefined the subject and content of this response or data.  

With GraphQL, clients can define the shape and structure of the response and request only the specific data they need. 

Endpoint structure:

In a REST API, each resource typically has its endpoint (URL). To access and retrieve different pieces of data or any additional information, clients must make separate and multiple requests to different endpoints.

In GraphQL, there is a single endpoint for all interactions. Clients can request numerous resources and related data in a single query. This minimizes the number of requests needed to obtain the required information.

Versioning:

In REST APIs, versioning is achieved by introducing new endpoints or using version numbers in the URL. Changes to existing endpoints can break backward compatibility and create issues with maintaining and evolving APIs.

GraphQL APIs are inherently versionless. Clients can request new fields or structures without breaking existing implementations. Backward-compatible changes can be introduced without the need for versioning. This promotes flexibility and easier evolution of APIs.

3 popular real-world applications of GraphQL

1. GitHub

GitHub provides a wide range of features, and different applications or integrations may have varying requirements. GraphQl allows clients, such as front-end applications or integrations to tailor their queries to retrieve only the necessary information. GitHub leverages GraphQL’s support of subscriptions to provide users with real-time notifications and updates, such as changes to repositories, pull requests, or issues. GitHub uses GraphQL to provide fine-grained control over pagination, enabling clients to specify the number of items per page and navigate the paginated results efficiently. This addresses challenges often associated with paginated data in REST APIs.

2. Shopify

Shopify is a popular e-commerce platform that adopted GraphQL to enhance its storefront API. Merchants can customize their online stores by requesting and modifying data that suits their specific requirements using GraphQL.This allows them to provide tailored and unique experiences to their customers. Merchants can leverage GraphQL’s real-time data updates by subscribing to store relevant events, such as new orders, inventory changes, etc., and receive real-time updates when they occur. This helps them keep their store data synchronized. 

3. Facebook (now Meta)

Facebook extensively uses GraphQL in its mobile applications. It enables clients to define the structure of the response, enabling flexible queries. This is of significant value to an application where different components of a page or application require different sets of data. Facebook uses GraphQL’s subscriptions abilities for its features like real-time notifications, live comments, and other interactive elements. GraphQL allows Facebook to consolidate its diverse data sources into a single API, simplifying the client’s interaction with the backend. Facebook’s Open Graph API, which provides programmatic access to various Facebook features, is implemented using GraphQL. This enables developers to retrieve user information, interact with Facebook’s social graph, and perform actions like posting updates, uploading media, etc. 

Conclusion

GraphQL has emerged as a transformative force, revolutionizing how data is queried, retrieved, and manipulated. As we’ve explored its real-world applications in this article, it has become evident that GraphQL is not merely a technological innovation but a strategic tool for organizations looking to meet the demand of modern data-driven applications. From social media platforms to e-commerce websites, GraphQL is reshaping the digital landscape, one query at a time. Taking a cue from these 3 technology trendsetters, it’s time you consider how you can integrate this powerful tool in your organization’s data lifecycle.