A little bit of background
It all began in the early days of computing when computers were massive, standalone machines. Communication was limited, so there was no need for standardized interfaces yet. The computers were primarily used in isolated environments for specific scientific, engineering, or business applications.
It was only as technology advanced and networks were established that they became more interconnected, and communication between them became more practical. As a result, there was a need for a common language to communicate effectively, making way for the first APIs. These early APIs, although mostly proprietary and limited to specific hardware or software systems, were in the form of libraries and protocols. This means that the developers could access certain functionalities or services either by using pre-written code libraries or by following specific communication protocols.
The current state of APIs
Today, the concept of APIs expands beyond the web—mobile apps, cloud computing, and the Internet of Things (IoT) all rely heavily on APIs to function effectively. They serve as the bridge connecting different software systems and enabling them to communicate and exchange data. In short, APIs have become a fundamental building block of modern software development as they allow developers to access and use services provided by external platforms.
At the same time, non-technical users can seamlessly integrate and leverage external services, data, and functionalities within their applications or systems using APIs. A weather forecasting API integrated into a mobile weather app is one of the most common examples that explain how APIs enable communication. In this case, the API provides real-time weather data from external sources, allowing the app to display up-to-date weather information to users. Without the API, the app would have to collect and update this data itself, which would be both resource-intensive and less reliable.
As the digital landscape continues to evolve, the demand for efficient and flexible APIs grows exponentially. Two of the most commonly used API architectures are REST (Representational State Transfer) and GraphQL. So, should you use REST or GraphQL? Let’s find out.
Like any other API, A REST or RESTful API is essentially a set of rules and conventions that dictate how web services should work and communicate with each other. It’s like a standardized language that allows different software systems to talk to one another over the internet using the HTTP protocol.
By design, these APIs are simple, scalable, and stateless, meaning each interaction carries all the necessary information for a request, so the server doesn’t need to remember previous requests. For instance, if you need to access data on a social media platform, you can easily do so using a RESTful API—you can send HTTP requests to retrieve user profiles, post updates, or perform various actions, all following a consistent structure and approach. This uniformity and simplicity in communication make RESTful APIs a widely adopted choice for building interconnected web services and applications.
REST has been the dominant API architectural style for years. One of its standout benefits is its simplicity. When working with RESTful APIs, you’ll find that the concept is straightforward and easy to grasp. For example, in REST, everything is treated as a resource, and each resource is uniquely identified by a URL (Uniform Resource Locator). This makes it easy to understand how to access and manipulate resources in an API—it provides a consistent and intuitive way to navigate the API landscape.
Another benefit of using REST is that each request you make to a RESTful endpoint is independent, meaning it does not rely on previous interactions. It also doesn’t need to maintain session-specific information on the server. Instead, each request contains all the necessary data for the server to process it, simplifying server-side logic. This is called stateless communication between clients and servers.
So, when a user accesses a product page on, say, an e-commerce website that uses a RESTful API, the server doesn’t need to remember the user’s past actions; the request to access the product page contains all the information required for the server to respond effectively.
Caching is another area where REST truly shines. It involves storing responses from the server and reusing them for subsequent identical requests. It’s particularly valuable in scenarios with limited bandwidth or high user traffic as it reduces the load on the server. Let’s say you’re developing a weather app that fetches weather data from a RESTful API. Instead of repeatedly making redundant requests to the API, you can use caching to store weather data for specific locations and serve it quickly to users.
All is not glamorous with REST—it has its fair share of downsides, especially when it comes to requesting specific information from a website. REST is notoriously famous for its high potential for over-fetching or under-fetching data.
So, when you request a blog post from a website, the API may fetch all the available data, including, for example, the author’s details, comments, and related posts. However, in some cases, you might only need the post content. This leads to over-fetching, as unnecessary data is transferred over the network, consuming bandwidth and increasing latency. Conversely, if you need additional information, such as the author’s bio, you’ll have to make further requests, resulting in under-fetching and multiple round trips to the server.
But that’s not all. Handling changes and updates to RESTful APIs can be challenging, often necessitating versioning in the URL. However, making substantial modifications to an existing API endpoint, whether to add a new feature or change a response structure, can cause the clients to experience issues or errors. This happens because these clients were built to interact with a specific version of API. Developers often introduce version numbers in the URL, such as /v1/posts and /v2/posts, to address this issue and ensure backward compatibility. Having said that, managing multiple versions becomes cumbersome and leads to code redundancy over time.
GraphQL is a query language and runtime for APIs that you can use to request exactly the data you need, making it highly efficient and flexible for fetching information from servers. It enables you to create queries specifying the shape and depth of the response, which is particularly beneficial when dealing with complex data structures or optimizing for mobile applications.
For example, in a social media app, you can use GraphQL to request a user’s name, profile picture, and recent posts in a single query, avoiding unnecessary data retrieval.
As a developer, you can use GraphQL to request only the data you need for a particular operation. This fine-grained control minimizes both over-fetching and under-fetching. For instance, for an e-commerce app, you can use GraphQL to create a query that explicitly requests only the product name and price for a product listing. This query allows you to optimize data transfer and improve performance by ensuring you receive only the essential data you need for that particular scenario.
GraphQL uses a single endpoint for API interactions, which simplifies the API structure compared to REST, where you typically have multiple endpoints for different resources and actions. When all queries and mutations are sent to a single endpoint, it becomes easier to manage the API as a whole, as the need to memorize a variety of URLs is reduced.
Using GraphQL, you can receive real-time updates as they occur, making it ideal for building features like live chat, notifications, or dynamic dashboards. For example, in a messaging app, you can use GraphQL subscriptions to push new messages to users in real time, creating a more engaging and interactive user experience.
While GraphQL offers many benefits, it does come with some weaknesses. One notable challenge is the learning curve associated with its query language and concepts, which are often daunting for newcomers. Understanding how to construct queries, define types, and work with resolvers can take time and effort to grasp fully, especially for users with non-technical backgrounds. This initial learning phase can also be a hurdle for developers transitioning from REST or other paradigms.
Another area where GraphQL suffers from lackluster performance is security. GraphQL schemas are highly customizable, which can be a strength but also a vulnerability if not carefully designed. Overly permissive schemas can expose sensitive data or allow malicious queries to overload the server. For example, if an e-commerce GraphQL API doesn’t have adequate access controls, an attacker could craft a query to access other users’ private order information.
Lastly, GraphQL’s flexibility, while advantageous, can also lead to complexity if query depth is not adequately limited. A deeply nested query with multiple levels of related data can quickly put a strain on the server. So, if your query requests a user’s posts, comments on those posts, and likes on those comments, it could result in a complex and resource-intensive operation, resulting in performance issues.
Should you use GraphQL or REST?
When deciding between GraphQL and REST for your project, it’s essential to consider the specific needs and trade-offs associated with each. Ultimately, the choice should align with your project’s specific demands because there’s no one-size-fits-all approach when it comes to APIs.
As we’ve seen above, GraphQL shines when you require flexibility in data retrieval and have varying or complex data requirements. For instance, in a social media platform, different parts of your app may need different sets of user data, such as name, profile picture, recent posts, and followers. GraphQL allows you to construct a single query specifying these data points, preventing over-fetching or under-fetching.
On the other hand, if your API has a stable data structure and well-defined, resource-oriented endpoints, REST can be a more straightforward choice.