What Is GraphQL? How it Solves Problems? Advantages of Using It
Before starting this topic, let me tell you one thing that this is going to be a long and detailed post. It will clear your lots of queries about GraphQL. So, read this post till the end. So, let’s start.
What Is GraphQL?
It is a query language used for API, and it provides a detailed and understandable description of data in your API. It becomes a powerful developer tool and enables clients to ask for exactly what they need. Moreover, when you send a query to API, you get exactly what you look for. GraphQL queries always provide the predicted results.
It has been observed that Apps which use GraphQL are stable and fast because they only control the data, not the server. Moreover, it provides many resources in a single request. For example, GraphQL queries not only access one resource’s property but also access the references between them.
GraphQL is a powerful option, and it gets all the data that the app requires in a single request. If you have slow internet connections, the apps using Graphql will still be quick.
The Basics of GraphQL
GraphQL is syntax and teaches people how to ask for data. Moreover, it’s used to load data from server to client. It has three main characteristics, such as:
When you get data from multiple resources, it makes aggregation easier.
Clients get the information they need.
For describing data, it uses the type system.
The Problem That GraphQL Is Trying to Solve
GraphQL solves the problems of REST. So, let’s have a look at the problems that GraphQL solves.
Let’s suppose we want to fill a page, and we want to show a list of posts and related comments and users on that page; what will we do?
Using REST API
If you’re using REST API, you have to make multiple requests to get all the information on that page. For this, you’ll have to:
Make extra requests for fetching users
For fetching M comments, you’ll use M request
If the posts have multiple comments, you’ll have to make lots of requests. This common problem is called the N+1 problem. This problem usually appears when we fetch a simple resource, and meanwhile, we have to make N requests to fetch the needed information.
So, how to solve this issue?
Use GraphQL because it enables us to get all the information in a single request. It will provide a list of all the posts in a single request. It’s an excellent advantage of GraphQL over REST.
Overfetching and Underfetching
Again, we’ll take the above-mentioned example. Suppose we have to fill out a page with a post’s list, and we have to show details like title, username, and tags on that page. When we use REST API, we have an endpoint.
We only need the title of the post, username, and tags on the new page, but we under-fetch and over-fetch data. We under-fetch data to fetch the user’s username and we have to request another endpoint.
Similarly, we over-fetch data because some attributes like image, body, and likes are not used on the page. It’s the main problem with REST API, and you have to specify lots of endpoints to get detailed information. Once we fix the endpoint, there is a possibility of getting either more or less data than we need.
How to solve this problem?
GraphQL is the solution because it allows the client only to specify the data that it needs. So, we’ll not have to face the problem of Underfetching and Overfetching data. With a single query, we get what we need without Overfetching and Underfetching data.
Frontend Coupled with Backend
Suppose we have to develop a new page in App; we need to call several REST API endpoints to get everything we need. If our goal is not to affect the App’s performance, we’ll try to make changes in REST API endpoints. Moreover, we’ll try to create a new endpoint to get the data we need for a particular page.
We encounter this problem in REST API. We have two options. The first is to make changes in API, and the second is to adopt frontend information that REST API provides. In this way, we couple our frontend with the backend, and it’s a problem.
In contrast, in GraphQL, clients can easily get data without doing anything at the backend. The client only needs to know the Schema of GraphQL API. Clients get all the information they need, and they can consume the information they want.
Lack of a Contract between Backend and Frontend
REST API defines how a server and client can communicate, but it doesn’t provide information about how the data structure can exchange information between server and client. This decision is open and easy, and the backend decides the way in which information can be sent and received with a client.
In other situations where we use external REST API, we don’t get the idea of data structure until we start using API.
In contrast, GraphQL has a strong type system. It clearly defines the information and data structure that clients can consume. Furthermore, you can write all these definitions in Schema GraphQL Definition Language (SDL).
Here, the Schema acts as a contract between server and client. After defining Schema, frontend and backend teams have nothing to do with each other, and they work independently. Moreover, the frontend team can follow this Schema and develop a complete web page or frontend App. Once the backend is ready, the team at the frontend can use real GraphQL API.
Lack of API Usage Tracking
When we use REST, we can only track how often clients call endpoints and consume API. In contrast, in GraphQL, the clients specify the information they need, and it gives us an indication about the data being used. Moreover, we can also measure the performance of each attribute. In this way, we can get detailed performance insight of API.
API Without Documentation
You can use tools like Swagger for creating documentation of REST API, but REST doesn’t make it mandatory to create documentation of each API. It’s easy to create documentation, but it isn’t easy to maintain that documentation. This is the reason; most REST APIs are either without documentation or outdated documentation.
On the other hand, GraphQL has a strong type system, and by definition, it’s a documented language. When we create Schema GraphQL, we get our API documentation.
So these are the problems that GraphQL solves and makes the developer's life easy.
Advantages of Using GraphQL
It offers lots of advantages over REST API. Some major advantages of using GraphQL are given-below:
GraphQL is faster
It’s much faster than other communication APIs because it cuts down the request query and only chooses the specific fields to provide results.
Ideal for Complex Systems
It allows you to integrate multiple systems with GraphQL APIs. GraphQL unifies them and makes them simple. It fetches data from existing systems and provides it in GraphQL response format. It’s best for third-party APIs and legacy infrastructures because they’re bigger in size and not easy to handle and maintain.
Avoid Problems of Over-fetching and Under-fetching
The main advantage it offers over RES APIs is the REST responses sometimes contain either not enough data or too much data. In both cases, you have to send another request. The good news is GraphQL only fetches the requested data. More importantly, it does this in a single request.
Defines Data Shape
When our GraphQL queries are sent to the server, we get responses in a secure, predictable, and simple shape. In this way, you can write a specific query according to your requirement. Therefore, GraphQL is easy to learn and use.
Another advantage of GraphQL is it follows the hierarchical structure, and it defines the relationships between objects in the graphical structure. In GraphQL, every component is represented by object type.
As mentioned earlier, it’s a strongly typed language, and each GraphQL query gets a particular response. In working, it’s similar to SQL, and you get a descriptive error message before executing a query.
Another interesting benefit of GraphQL is it allows sharing codes at higher component types for reuse. It is called a fragment and gives different data while maintaining the same schema field.
GraphQL Is a Protocol
They don’t provide any backing storage because it takes advantage of existing code.
It’s a powerful platform due to its supporting types. Its supporting types are Relay, application framework, and GraphiQL. GraphiQL enables developers to develop and explore an API quickly.
No Need for Latest Version
GraphQL returns data according to the client’s query. Therefore, the server can easily generalize it. The addition of fields and features to the server won’t affect the existing clients. In GraphQL, you can use the older version without any tension. You don’t need to upgrade to the latest version. You might have observed that Facebook is still using the same GraphQL API in their Apps.
Challenges of Using GraphQL
GraphQL is widely used because it solves many problems associated with REST APIs. It offers many benefits, but meanwhile, it has some challenges as well. So, let’s discuss the challenges associated with GraphQL.
When you perform coding in the backend, you realize that it contains lots of similar but not identical codes, especially in GraphQL Schema. You need one schema for your GraphQL endpoint and the second one for your database.
Now, the challenge is you have to write almost the same thing twice, and you have to keep both of them in sync.
How to fix it?
You can use PostGraphile for generating a schema from your database.
GraphQL Makes Some Tasks Complex
If the application is simple, it’s not recommended to use GraphQL because it can add more complexity due to queries, types, resolvers, mutators, and high-order components. All these things are not good from a maintenance perspective.
Still, if you want to use GraphQL, there will be two complications, such as error handling and file uploading. In contrast, you can easily check the response status and identify the server error if the resource isn’t found.
How to fix it?
You can handle errors in GraphQL by using libraries like Apollo client. You can either use a separate server or use a library like the Apollo upload server for file uploading. You can also add another dependency for managing your project, but it might not be available for all programming languages.
It’s easy to implement cache at the database level, but it can be challenging to implement cache at the web level. When you implement cache at the HTTP level, the amount of traffic to the server is reduced, and the information is located close to the client. GraphQL has only one endpoint, and all the queries are sent to it. Most of the queries are different, so it becomes difficult to use such caching.
How to fix it?
You can use persistgraphql to reduce the amount of traffic on the server. It’s a good solution, but it increases the complexity as well.
GraphQL is a query language, and it enables clients to execute queries and get what they need. The question is, will it still be useful if a client asks for lots of resources and fields? For complex queries, it’s not ideal because it has only one endpoint.
REST API has multiple endpoints, and you can specify your queries to get results efficiently. It can be a time-taking process, and if not done right, it can have a bad impact on your server. For example, it can slow down the server speed.
How to fix it?
You can use tools like Dataloader to cache database calls. There is a possibility that it might not work in some situations, and you might have to block queries. So, you’ll have to choose a solution according to the library.
Not Wise to Use it for Small Applications
First of all, one thing should be clear that GraphQL is an alternative to REST API, and it’s not the replacement. Clients send the query and get exactly what they need. It’s also doable in the REST. You can use JSON API Libraries to implement it. JSON Schema can be beneficial. As mentioned at the start, it’s ideal for complex and third-party APIs, but when it’s used for small applications, it can’t be a wise practice.
What’s the alternative?
You can try OData. In some situations, it won’t be easy to use these libraries. Therefore, the best way is to use GraphQL because it supports lots of features. Meanwhile, it can also make things complicated. You need to decide wisely whether you need GraphQL or go with any other option.
Difference between REST and GraphQL
In GraphQL, the identity is separate, and you can easily fetch it. In contrast, the endpoint you call is the identity of that object.
GraphQL has one endpoint and provides the needed information. In contrast, REST has multiple endpoints, and you get either more or less information.
In REST, the server determines the shape and size of the resources. On the other hand, in GraphQL, the server declares available resources, and clients can ask for the information they need.
GraphQL is ideal for complex applications and tasks because it has only one endpoint. In contrast, REST APIs are ideal for smaller applications.
Rest is useful when the client asks for multiple resources at a time.
In GraphQL, there is no issue of over-fetching and Underfetching, and you only get what you need. In contrast, in REST APIs, you get lots of extra information.
Difference between GraphQL and RPC
GraphQL is a flexible system, and it delivers what is required. Contract negotiations in RPC make it different from GraphQL.
RPC is lightweight, and GraphQL is flexible and adaptable.
GraphQL is client-driven, and the client handles everything. In RPC, power is on the client-side, but the handling is done by the remote server hosting.
RPC runs on contracts, and the negotiation is done between the client and server. In contrast, GraphQL uses the schema to fetch the required information.
RPC learning curve is easy, and the learning curve of GraphQL is slightly difficult.
GraphQL is used in microservices, mobile APIs, and complex systems. RPC is used in command and action-oriented APIs.
GraphQL is organized in terms of schema and type system. In contrast, RPC is organized in terms of local procedure calling.
GraphQL Vs gRPC Vs Protobuf
In GraphQL, the user defines the format and expected data. In contrast, gRPC is good for processing a set amount of data.
GraphQL offers information in a single request. On the other hand, gRPC works with protocol buffers. Protobuf is a system that is used to serialize or de-serialize the data.
In Protobuf, all the data is in binary format, so it is lighter than GraphQL JSON.
The main difference between the two is flexibility and efficiency. The gRPC is good for performance, and GraphQL is critical for quickly evolving APIs.
Developers feel that gRPC is 10 times faster than GraphQL based on some conditions.
Developers look for power tools to integrate different data resources, and GraphQL is one of them. Now, you don’t have to use traditional REST APIs because they’re not efficient. Since it was used in Facebook, which is a complex application, and since then, it’s mostly used in complex applications.
We have compared different tools to make it easy for you to decide. Yes, it’s an effective tool and has some excellent advantages, but meanwhile, you must be aware of the challenges it poses. You can’t pick a tool based on one factor; you have to take everything into account before making a final decision. Once you understand the difference between these tools, you can easily choose a tool according to your needs.