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GraphQL vs. REST API: Which is better for querying data?
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GraphQL vs. REST API: Which is better for querying data?
Choosing the best API for compiling data can seem overwhelming if you don’t know how well they perform on a larger database. Developers typically use them to exchange data between programs and build functionality for their web apps. This makes it possible for the front-end and back-end teams to communicate better and develop products for consumers.
The top two APIs are GraphQL and REST, each with its own pros and cons for sending a request and retrieving the result. GraphQL is considered an open-source data query and manipulation language for APIs, whereas REST is defined as an architectural standard for interacting with localized software services.
As a developer, you might be curious about the potential use cases of both, as they provide a seamless environment for testing new features. Ultimately, this comes down to the scope of your project and what problems you’re trying to solve.
This article will explore how they compare on multiple fronts, from fetching relevant information to sorting entries by category.
Properties of REST API
REST diverges from GraphQL in that requests are grouped via endpoints and mutations can have any format besides string. It relies on a GET command to fetch resources (JSON response), which requires making multiple API calls to grab separate search results. Likewise, it is server-driven rather than client-driven architecture stacked into layers of hierarchy.
Here are the key features of REST API:
Each HTTP status code points to a unique response
The server determines the shape and size of resources
Ability to cache on the browser or server with a CDN
Has a uniform interface that decouples the client from the server
Plenty of flexibility since calls are stateless and do not depend on each other
Benefits of REST API
REST works best on media files, hardware or web elements, mapping a linear path to those resources. A REST API will boost its performance by scaling to client demands and is capable of locating resources by name. It is built for storing common data types in memory and can be deployed from several servers in one sitting.
With REST API, you get the opportunity to develop apps in all kinds of environments, due to how it integrates with a wide range of frameworks. It has been implemented in languages including Python, Java, PHP, and Ruby, enabling you to perform operations or create object instances explicitly over the protocol.
On the bright side, you can easily migrate from one server to the next, or even build a portable UI across platforms and OSes. REST is ideal for automatic HTTP caching, reporting on errors, and has you covered against DDoS attacks. Nonetheless, its simplicity has some merit, being that it’s easy to extend and modify for connecting to other apps or services.
Properties of GraphQL
On the other hand, GraphQL overcomes the hurdles presented by REST, as it allows the user to make targeted queries using a POST request. This is directed toward a single URL endpoint and returns the matching result if it exists in the database. GraphQL is instead arranged by schema, so the identity won’t match its fetch method. To validate queries, it will scan the cached metadata, an option not supported by REST.
Here are the features that define GraphQL:
A self-documenting model that conforms to the client’s graph data
The server dictates which resources are open to the user
Reduces overhead communications with API providers
Selects the type of operation using a keyword on the schema
A request executes multiple fields that converge at the same endpoint
Advantages of GraphQL
GraphQL brings many benefits to the table, shaping JSON data into a readable syntax. It expresses more consistency across operating systems, boasting faster development speeds on all platforms. It is capable of decoupling the front end from the back end to encourage work done on independent projects. To drive productivity, front-end iterations are no longer tied to back-end adjustments, placing less burden on the server.
It’s also strongly typed, limiting queries to certain data types based on context. This API is designed to help you with query batching and caching by merging SQL queries to prevent a session timeout. You can look at what each function does and create custom requests to meet your users’ needs. In terms of upkeep, GraphQL will sync to updated documents and maintain version control without manual input.
One advantage of GraphQL is the removal of excess data to prevent over-fetching on the fields you specify. On the flip side, you could run into under-fetching and not extract enough JSON values from an endpoint. This doesn’t happen on GraphQL because once a query is sent, the server reveals the exact data structure.
Examples of When to Use GraphQL
GraphQL is suitable for creating cross-platform apps that customers can access on a mobile phone. Its schema is designed for chaining longer query objects on the client side, helping you gain a better understanding of how data is extracted.
GraphQL is used to enhance mobile app performance by reducing load times with fewer calls. It expands your API functionality to remedy issues reported on older versions.
Schema stitching is quite convenient for modifying the client side since multiple schemas are combined into one to complete a data source.
Let’s look at a few sample queries:
Type Novel {
id: ID
title: String
genre: Genre
author: Author
}
Type Genre {
id: ID
published: Date
genres: [“Fantasy”, “Science Fiction”, “Non-Fiction”, “Adventure”, “Mystery”]
novels: [Novel]
}
While this example describes the fields under a Novel type, it does not give away how the object is fetched from the client. You still have to construct a Query type to access the values of a novel by its author or genre.
Many applications require you to add, delete, or update data on the backend. This is achieved by utilizing three types of mutations.
Here is how you declare a mutation:
First, use the mutation keyword to create one that resembles a standard query. For each field, it can take any number of arguments.
mutation {
rootField(arg1: value1, arg2: value2) {
arg1
arg2
}
}
This root field passes in two parameters that return a specific output. Next, you’re able to assign different properties to the mutation object which will show up in the server response.
Disadvantages of GraphQL
GraphQL isn’t without its problems. Its single endpoint lacks caching, which is possible with a GET request, meaning that you have to implement browser caching for non-mutable queries. In some cases, GraphQL mutations can become buried under a flood of data types. Although you can pull up exact queries, you have no say over third-party client behaviors.
Search operations like joining queries are more complicated than on REST microservices that route requests over a web host or URL. By default, GraphQL’s rigid queries are difficult to model for advanced aggregations or calculations. As for security, monitoring on GraphQL is practically nonexistent because only a few SaaS contain those API analytics.
Examples of When to Use REST API
A REST API is your best bet if users need to submit requests as separate URLs to retrieve data from microservices architecture. For projects smaller in scope, you can save memory space by importing its tools on your desired framework to designate unique ids on a handful of calls.
If you’re not too fixated on collecting insights or dealing with backward compatibility, REST will do a good enough job.
Generally speaking, a REST request comprises of the header, body, endpoint, and HTTP method for managing the standard CRUD operations.
To initialize a basic call, you should do the following:
response = requests.get(“https://siteurl.com/path.json”)
print(response.json())
The output to the body section:
{
“parameter 1”: “value 1”,
“parameter 2”: “value 2”,
“parameter 3”: “value 3”
}
A successful request will return code 200 and display the types of fields (strings, integers, dictionaries) stored in that library.
REST resources are distinguished by their URLs, which are recovered by delivering JSON to the server (i.e. GET, POST). To illustrate, we will perform an API call that reaches the endpoint of a user profile.
Let’s jump into posting JSON to the server:
{
“Id”: 529387,
“Name”: {
“First”: “John”,
“Last”: “Brown”
},
“Age”: 24,
“Occupation”: “Research Associate”
}
In the above example, a response returns the output of an employee who works at a biotech company. To update these fields, you also need to set the MIME type for the body to application/json.
Drawbacks of REST API
After mobile’s rise to popularity, REST was deemed too inflexible to address network issues. Simply put, it struggled to convert app data to a graphical form by attempting to scale its unstructured parameters. If you want to grab a specific attribute, you have no choice but to create new resources and modify them across multiple roundtrips.
Because REST is server-driven, clients are entirely dependent on network conditions. It often leads to nested N+1 queries, chaining API calls on the client, and making the returned URI harder to read. It introduces delays in the development lifecycle where front-end teams must wait for back-end teams to deliver the API, thereby pushing back product release dates.
Conclusion
The main takeaway from all this is that GraphQL and REST API serve different purposes in the app development lifecycle. GraphQL gives the data you’re looking for without over- or under-fetching and is compatible with advanced techniques like transforming fields into different values. REST is easier to implement on JS frameworks if you plan to locate a precise resource or design an interactive website.
An important thing to remember is they both have advantages and disadvantages depending on the product specifications as well as the user requirements. GraphQL may have the upper hand in an agile environment, but it still has room for improvement. REST has more existing tools and integrations; however, it can be affected by poor network conditions.
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