Understanding GraphQL – A Basic Way / Blogs / Perficient

Introduction

It would be an understatement to say that GraphQL is a paradigm shift for data queries. There is no comparison between the two; rather, it is more like the difference between walking and flying. Take a look at how GraphQL differs from conventional REST APIs to see why.

Traditional REST queries require several requests to retrieve all the necessary data, and as your service scales, it will become increasingly difficult to manage them. With GraphQL, you can quickly specify complicated data requirements and query exactly what you need with a single request- not to mention potential support for real-time subscriptions.

Therefore, join us as we take a deep dive into understanding everything about GraphQL it’s enhanced performance, easier integration between clients, quicker development times, and lower maintenance costs sound attractive.

What is GraphQL?

GraphQL, which stands for Graph Query Language, is not a language for talking directly with a database like SQL (Structured Query Language), but rather a language that establishes a contract via which a client talks with an API server. The rules and traits of the language are described in the open standard known as the GraphQL specification. It also offers guidance on how to run a GraphQL query.

GraphQL has no official implementation because it is outlined under an open standard. As long as it adheres to the norms given in the specification, a GraphQL implementation can be created using any programming language, integrated with any kind of database, and supported by any client (including mobile and online applications). Although Apollo GraphQL, one of the most widely used commercial GraphQL implementations, boasts many GraphQL client and server implementations, it is not required to use Apollo to use or comprehend GraphQL. Facebook created GraphQL in 2012 (and made it available to the public in 2015) to address many issues with traditional REST architecture by creating a new, declarative, client-driven, and performant system.

GraphQL enables you to make one call and obtain the data you require fast and effectively rather than having an endpoint for each sort of data a client might require. The following are some advantages it has over conventional REST APIs:

Faster development time: Developers spend less time writing code since GraphQL’s syntax is simpler to understand and use.

Improved performance: It speeds up the server’s response time to let clients make a single request for all the data they require.

Reduced maintenance costs: The requirement to monitor numerous endpoints is diminished when a single GraphQL endpoint is used, which simplifies server maintenance.

GraphQL: A rapidly growing community

Since many businesses, including Netflix and Coursera, are interested in and working on related projects to improve this API, the community for GraphQL is constantly and rapidly expanding. Coursera terminated its initiatives and shifted entirely to using GraphQL after GraphQL got open-sourced. Netflix also open-sourced its Falcor solution.

Many businesses now use GraphQL, including Github, Pinterest, Twitter, Facebook, Coursera, Yelp, Serverless, Shopify, ProductHunt, etc.

How does GraphQL work?

GraphQL is primarily used to create APIs. It uses a type system to specify the types of data and how they can be accessed. Users can specify the data they require in a single request using GraphQL, and it will be returned as a JSON response.

GraphQL consists of three components:

The Query Language: Developers use this to specify the data that a client needs from the API.

The Schema Definition Language (SDL): Developers use this to provide the data structure that can be requested via the API.

The Resolver: The server uses this to handle the GraphQL queries and return the requested data.

Because of GraphQL’s extreme flexibility, developers can add or delete fields from a query without having to alter the underlying code. As a result, fewer endpoints are required, and updating a data structure is made easier.

GraphQL Example:

Let’s examine a GraphQL usage illustration. Consider a server that has both fiction and nonfiction books. You would have to submit two different queries for each type of book if you used a conventional REST API. Using GraphQL, you can specify all the data that the client needs in a single request.

To make a GraphQL query, you must first define your desired data type. This is done with what’s called a schema. The schema describes how the available data is structured and how it might be integrated. Clients can use a query to retrieve the information they require once the type system is defined.

Let’s have a look at an example of a GraphQL query. An illustration of GraphQL is shown below:

query {
    FictionBooks {
        name
        author
    }
    NonFictionBooks {
        name
        author
    }
}

This query provides the client’s request in a single response. The Resolver is then used by the server to process the request and deliver the required content. With the help of GraphQL, developers can create robust APIs that give customers the information they need in a flash.

Sample Output:

FictionBooks {
        "name": "Lone Women";
        "author": "Victor Lavalle"
    }
NonFictionBooks {
     "name": "Silver Haze";
     "author": "Pankaj Varma"
    }

GraphQL Vs Rest:

Although the principles of GraphQL and REST are not interchangeable, they help applications with comparable issues. Representational State Transfer, or REST, is a software architectural approach for transferring data among various systems. An API that follows the REST guidelines is said to be RESTful. These guidelines include providing a uniform interface, such as using URIs, being stateless and cacheable, and ensuring a separation of concerns between the client and server. As mentioned before, GraphQL is a specification for a query language and runtime for carrying out inquiries.

Both approaches have benefits and drawbacks, and both are used in the development of modern APIs. However, GraphQL was created to address some alleged REST system flaws and to produce a more effective, client-driven API.

Architecture:

GraphQL exchanges data through a single endpoint in contrast to the numerous endpoints that usually make up a REST API. A GraphQL endpoint can return a complicated graph of data that might need many REST queries, reducing the number of requests over the network for a single view.

Data Fetching:

A REST API returns the selection of data that the server determined. If the view only needs one property from a response, for example, this may be significantly too much data. Additionally, it might not be sufficient in some cases, such as when a list endpoint doesn’t return all the properties that a table needs in the view. Declarative queries in GraphQL stop data from being fetched too much or too little.

Error Handling:

There is no specification on the use of HTTP response codes for faults because it is not required for GraphQL to be provided over HTTP. All GraphQL APIs typically resolve with a 200 HTTP code response, and unsuccessful responses provide an errors field in addition to the data property. The HTTP status codes 400 and 200 used by RESTful APIs, in contrast, are distinct and indicate whether a response was successful or not for the client.

This list highlights some of the most significant REST and GraphQL similarities and differences but does not include all of them. Additionally, numerous REST endpoints or services can be combined using GraphQL as a gateway, enabling the harmonious coexistence of both technologies.

Conclusion:

In this article, you learned what GraphQL is, the key differences and similarities between GraphQL and REST, and how a GraphQL server exposes data to a client. I hope you enjoyed reading this post and found it to be useful.