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GraphQL vs REST for Building Backend APIs

As we navigate through the world of backend development, there are numerous approaches and technologies to consider. In particular, the conversation often revolves around GraphQL and REST when it comes to building backend APIs. This article aims to provide a comprehensive comparison of these two paradigms, their use in Java and JavaScript, their advantages, and their disadvantages. As a testament to our commitment to cutting-edge technology at Lazer Consulting, we’ll delve into the reasons why we have chosen both in the past.

Understanding GraphQL and REST

GraphQL, introduced by Facebook in 2015, is a data query and manipulation language for APIs. It provides a more efficient, powerful, and flexible alternative to REST and offers some distinct advantages. Despite being a newer technology, it has quickly gained traction in the developer community due to its robust feature set and the ability to deliver a better performance.

On the other hand, REST (Representational State Transfer) has been a widely adopted standard for APIs since the early 2000s. It leverages standard HTTP methods like GET, POST, PUT, and DELETE and is built around resource-based URLs. While it has enjoyed widespread adoption, REST has its limitations, which GraphQL aims to address.

Using GraphQL and REST with Java and JavaScript

Both GraphQL and REST can be used with various programming languages, including Java and JavaScript, two popular choices for backend development.

For Java, there are libraries like graphql-java and Spring Boot for GraphQL, and Spring Boot and Jersey for RESTful services. JavaScript, a ubiquitous language in web development, provides Apollo and Relay for GraphQL, while Express.js and Koa are common for REST.

One of the main differences in using these technologies with these languages lies in their flexibility. GraphQL’s type system, which guarantees type safety, is easier to leverage in a statically typed language like Java. Conversely, JavaScript’s dynamic nature tends to pair well with the flexible data structures of REST.

Advantages and Disadvantages

GraphQL’s primary advantage is that it allows clients to define the structure of the data required, and the same structure of the data is returned from the server. This avoids the over-fetching and under-fetching issues associated with REST and is often more performant due to reduced payload sizes. Moreover, GraphQL allows for powerful queries, including for nested resources and arrays, which would require multiple roundtrips in REST.

However, GraphQL is not without its downsides. It requires a more sophisticated client to handle queries. Caching, a built-in feature with REST, is more challenging to implement with GraphQL. And because it is newer, fewer developers are familiar with it, and there are fewer resources and third-party tools available.

REST, on the other hand, is straightforward to understand and use, with ample documentation and community support. It naturally fits with HTTP, leading to features like stateless servers and structured access to resources. However, REST can be more verbose, requiring more data to be transferred, and it often necessitates multiple round trips to the server to retrieve nested data.

GraphQL: The Cutting-Edge Choice

Despite the advantages of REST, a growing number of developers are migrating towards GraphQL. While concrete usage statistics are challenging to come by, various industry reports and surveys suggest that GraphQL’s adoption rate is rapidly increasing. GitHub, Shopify, and Yelp are a few among many that have transitioned over.

At Lazer Consulting, we choose to adopt GraphQL because it allows us to use the latest technology to provide efficient and high-quality solutions for our clients. By leveraging GraphQL’s benefits and continually staying updated with its improvements, we ensure our clients receive the most advanced solutions available.


Both GraphQL and REST have their strengths and weaknesses so none of them is the perfect choice all the time.

As many tech services and technologies around, it depends a lot on the tech stack used, the business logic inside, the efficiency and optimisation you desire and what the application is supposed to do.


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