Today, when we think about conventional web design, RESTful has become the standard in the industry for the design of API. REST is wonderful, and it or something like it is essential for the growth we see in web design. Today, I ask: where would we be without stateless servers and structured access to resources? These concepts have driven the evolution of web development, but as times change, the technology landscape also shifts. Unfortunately, REST is starting to struggle to adapt to these new standards.
What Are the Alternatives?
Fortunately, we have several options, including Falcor APIs, JSON-Pure APIs, and OData APIs. Today, I want to focus on GraphQL and explore how it compares to RESTful APIs.
Data Fetching and Performance: REST vs. GraphQL
Let’s consider an example: a website that displays a user and their posts. Traditionally, to fetch this information via REST, you would need to make multiple requests.
First, an HTTP GET request to /users/ retrieves the user’s details.
Next, if you want the user’s posts, you make another request to /users//posts.
If you need additional user information, each piece requires a separate request.
While this process might seem tedious, it’s the standard protocol for RESTful APIs, which we’ve been using for quite some time.
The GraphQL Advantage
With GraphQL, you send a single query to the server specifying exactly what data you need. In return, you get a JSON object containing all the requested information.
The server responds with a JSON object that includes the user’s name, email, and their posts—all in one trip.
This approach significantly reduces over-fetching and under-fetching, which can have a major impact on efficiency and performance — especially in terms of Big O notation.
The Power of Schema in GraphQL
Another key advantage of GraphQL is its structured API, built around schemas. In a RESTful API, making schema changes can be complex and time-consuming, often requiring rollbacks, version control, and sometimes entire teams to manage updates.
In contrast, GraphQL schemas act as a contract between the client and server. Once defined, both frontend and backend teams can work independently, knowing exactly how data can be accessed and manipulated over the network.
This schema-driven approach increases development efficiency and reduces potential errors. Updating the schema is straightforward — it involves adding or removing fields as needed, without overhauling the entire API.
Final Thoughts
While these are just a few highlights, schema-based databases like GraphQL offer numerous benefits worth exploring. I encourage you to dive deeper into this technology, as it has the potential to significantly improve your company’s productivity and agility.