As developers, we’re always passionate about learning new things! Whether it’s a new framework or a new language, our curiosity takes us places! One term you may have heard of is REST. REST stands for REpresentational State Transfer - a software architecture style introduced by Roy Fielding in the year 2000, with a set of principles on how a web application should behave. Think of this as a guideline of operations, like how to put together a meal. One of the principles is that one endpoint should only do one CRUD action (either create, read, update, or delete). As well, each RESTful endpoint returns a fixed set of data. I like to think of this as a cookie-cutter response, where you get the same shape back every time. Sometimes you may only need less data, and other times you may need more data. This can lead to the issue of calling additional APIs to get more data. How can we get exactly the right amount of data and under one call?
As technology evolves, one thing that contrasts REST and is gaining popularity is GraphQL. But what is it exactly? Within this blog, we will learn what GraphQL is all about!
- Explain what GraphQL is.
- Use an analogy to deepen your understanding of GraphQL.
- Explain the difference between REST and GraphQL.
Before You Start
If you are new to API development, here are some terminologies for reference. Otherwise, continue ahead.
What is API?
Application Programming Interface (API) allows two machines to talk to each other. You can think of it as the cashier who takes your request to the kitchen to prepare and gives you your meal when ready.
Why are APIs important?
APIs allow multiple devices like your laptop and phone to talk to the same backend server. APIs that use REST are RESTful.
What is REST?
REpresentational State Transfer (REST) is a software architecture style on how a web application should behave. Think of this as a guideline of operations, like how to put a meal together.
Why is REST important?
REST offers a great deal of flexibility like handling different types of calls and responses. It breaks down a resource into CRUD services, making it easier to organize what each endpoint should be doing. One of REST’s key principles is client-server separation of concerns. This means that any issues that happen on the server are only concerned by the server. All the client cares about is getting a response back based on their request to the server.
What is latency time?
Latency time is the time it takes for your request to travel to the server to be processed. You can think of this like driving from point A to B. Sometimes there are delays due to traffic congestion.
Why is latency time important?
The lower the latency, the faster the request can be processed by the server. The higher the latency, the longer it takes for your request to be processed.
What is response time?
Response time is the sum of latency time and the time it takes to process your request. Think of this as the time it takes since you ordered your meal.
Why is response time important?
Like latency, the faster the response time, the more seamless the overall experience feels for users. The slower the response time, the less seamless it feels for users, and they may quit your application.
What Is GraphQL?
GraphQL is an open-source data query and manipulation language for APIs, released publicly by Facebook in 2015.
Unlike REST, GraphQL offers the flexibility for clients to describe the structure of the data they need in the form of a query. No more and no less. The best part is it's all under one endpoint! The response back will be exactly what you described, and not a cookie-cutter response.
For example, provided below, we have three API responses about the Toronto Eagles, their championships, and their players. If we want to look at the year the Toronto Eagles were founded, the first and last name of the team captain and their last championship, we need to make three separate RESTful calls.
When you make an API call, it’s ideal to get a response back within a second. The response time is made up of latency time and processing time. With three API calls, we are making three trips to the server and back. You may expect that the latency times for all three calls would be the same. That will never be the case. You can think of latency like driving in traffic, sometimes it's fast, and sometimes it's slow due to rush hour. If one of the calls is slow, that means the overall total response time is slow!
Luckily with GraphQL, we can combine the three requests together, and get the exact amount of data back on a single trip!
Here are two analogies to help describe how GraphQL compares to REST.
Analogy 1: Burgers
Imagine you are a customer at a popular burger restaurant, and you order their double cheeseburger. Regardless of how many times you order (calling your RESTful API), you get every ingredient in that double cheeseburger every time. It will always be the same shape and size (what’s returned in a RESTful response).
With GraphQL, you can “have it your way” by describing exactly how you want that double cheeseburger to be. I’ll take a double cheeseburger with fewer pickles, cheese not melted, bacon on top, sautéed onions on the bottom, and finally no sesame seeds on the bottom bun.
Your GraphQL response is shaped and sized to be exactly how you describe it.
Analogy 2: Banks
You are going to the bank to make a withdrawal for $200. Using the RESTful way, you won’t be able to describe how you want your money to be. The teller (response) will always give you two $100 bills.
By using GraphQL, you can describe exactly how you want your denominations to be. You can request one $100 bill and five $20 bills.
REST Vs GraphQL
Compared to RESTful APIs, GraphQL provides more flexibility on how to ask for data from the server. It provides four main benefits over REST:
No more over fetching extra data.
With REST APIs, a fixed set of data (same size and shape response) is returned. Sometimes, a client doesn’t need all the data. GraphQL solves this by having the clients grab only what they need.
No more under fetching data.
Sometimes, a client may need more data. Additional calls must be made to get data that an endpoint may not have.
Rapid product iterations on the front end.
Flexible structure catered to clients. Frontend developers can make UI changes without asking the backend developers to make changes to cater frontend design changes.
Calling too many endpoints can get confusing really fast. GraphQL’s single “smart” endpoint bundles all different types of RESTful actions under one.
By leveraging GraphQL’s principles of describing the structure of the data you want back, you don’t need to make multiple trips for some cookie-cutter responses. Read part two of Understanding GraphQL for Beginners as we’ll implement GraphQL to a Ruby on Rails application, and create and execute queries!
Often mistaken as an intern, Raymond Chung is building a new generation of software developers through Shopify's Dev Degree program. As a Technical Educator, his passion for computer science and education allows him to create bite-sized content that engages interns throughout their day-to-day. When he is not teaching, you'll find Raymond exploring for the best bubble tea shop.
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