Deep dive into GraphQL | Query Language for API

The number of interfaces between various systems likewise increases in tandem with the complexity of software applications. This results in an explosion of client-server integrations and an ever-growing API footprint.

This eventually leads to a maintenance nightmare. Even small adjustments start to take longer and longer to make. It would help if you did the additional analysis. Test more. Even then, there is a potential that problems will find their way into your application.

Refactoring your interfaces often seems to be the only way to deal with the issue of steadily rising maintenance expenses. Refactoring is an expensive endeavor, though. Therefore, management typically won’t authorize it unless there is a compelling argument.

That’s where GraphQL comes in as a potential solution for top backend development companies. GraphQL brings a paradigm shift in how clients and servers communicate with one another. While it is not a simple solution, it can serve as a middle ground between a total revamp of the program and doing nothing.

In this article, we’ll discuss GraphQL in detail, why it’s used the most by the web developers, and what it means for your business growth.

What is GraphQL?

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. It was developed at Facebook in 2012 and released as open-source in 2015.

The basic idea behind GraphQL is that you can ask for exactly the data you need and nothing else. This makes it faster than REST APIs because it doesn’t have to make multiple calls to different endpoints to get all of your data. It also makes it easier to maintain and update your code because you only make one call instead of many.

More of a format or structure, GraphQL serves to specify the terms of the agreement between the client and the API server. In essence, you may consider it a specification or a new API standard like REST.

The idea for GraphQL, according to co-creator Lee Byron, came about when they were attempting to create a native iOS news feed with a RESTful API. They instantly ran into a number of problems, some of which included:

• Slow API requests on the networks.
• Coordination between different model requests created problems.
• Precision required in API changes carried over to client code to avoid crash problems.
• Gap between the actual implementation of API docs.

The development of GraphQL was motivated by the desire to address the issues raised using standard RESTful APIs. 2015 saw the public release of GraphQL.

In the end, the project was transferred from Facebook to the recently founded GraphQL Foundation in 2018. The Linux Foundation, a nonprofit organization, is now the home of the GraphQL Foundation.

Aside from Facebook, where GraphQL continues to fuel API calls, hundreds of other businesses, including Credit Karma, GitHub, Yelp, PayPal, The New York Times, and more, employ it in real-world applications.

How does GraphQL works?

GraphQL uses the concept of a schema, which contains all the types and their relationships between them. A schema is written in JSON or YAML format and can be found in your API documentation. It’s a collection of data that defines the structure of your database.

The client sends queries to the server that describe what data it needs and how it should be formatted. The server will respond with exactly what the client asked for, no more and no less. This makes it possible to build an entire application around one or a few central APIs rather than many micro-services.

A client can verify their query against the schema before inquiring to ensure the server responds to the query. Although a GraphQL query’s form closely resembles the outcome, you can anticipate what will be given back. This gets rid of unpleasant surprises like missing data or a flawed structure.

After reaching the backend application, a GraphQL action is resolved with data for the frontend application and is interpreted against the whole schema.

GraphQL is based on graph data modeling and has three main actions at its core:

1. Query for reading data
2. Mutation for writing data
3. Subscription for automatically receiving real-time data

In short, the advancement GraphQL made is the ability to query in a single request and retrieve only the required data rather than the entire collection. The primary factor making GraphQL so appealing to developers is its client-driven design. Giving the clients GraphQL access to the data enables them to select which data to return.

In contrast, REST confronts the issue of over-fetching due to its belief that everything is a resource. The client must make repeated network requests to obtain all the information contained in a resource, even if they only need a portion of it. In this case, the server defines the available data for each resource.

Features of GraphQL

Here are some of the key features of GraphQL:

• You write the desired data and receive it exactly as written—no more excessive information retrieval like with REST.
• Schemas are created using a special language specific to GraphQL. Schema Definition Language (SDL) is a human-readable schema syntax. You can use the SDL with whatever language or framework you want; it won’t matter what technology you use.
• It provides a single endpoint; the same API is no longer available in versions 2 or 3.
• Because GraphQL is tightly typed, you can check a query against the type system before executing it. It aids in the development of more robust APIs.
• One of GraphQL’s most crucial features is its type system. Types are unique objects that represent the design of your API. For instance, if you’re developing a social media program, your API should support types like Posts, Users, Likes, and Groups.
• Use mutations to edit data on the server and receive updated data back in GraphQL. You can approach thinking like the REST CUD (Create, Update, Delete).

GraphQL vs. REST APIs

REST is a set of architectural principles, including the concept of resources, while GraphQL is a query language that enables developers to specify the data they need. Both are useful in their own right, but are often used together in modern applications.

The REST API was designed to create web-based interfaces between different software applications. A REST API provides a way for users to retrieve and modify data using standard HTTP requests.

In recent years, the popularity of REST has decreased as more companies have adopted GraphQL as their preferred API design pattern.

So here’s the difference.

Point of difference	GraphQL	RestAPI
Type of technology	Application layer server-side technology	Software architectural style
Follows	Client-driven architecture	Server-driven architecture
Way of arrangement	It can be arranged in terms of schema	It can be arranged in terms of endpoints
Community	GraphQL community is growing	RestAPI has a large community
Development Speed	Fast	Slow
Learning curve	Difficult	Moderate
Consistency across platforms	High consistency	Inconsistent
Message format	Must be a string	Can be anything
Endpoints	Single	Multiple

Advantages and disadvantages of GraphQL

Advantages of GraphQL

1. Declarative data fetching

   GraphQL embraces declarative data fetching with its queries. In a single query request, the client selects data along with its entities and fields from various relationships. Like how Airbnb uses it, GraphQL determines which fields are required for its UI and functions nearly as UI-driven data fetching. An Airbnb search page often displays results for houses, experiences, and other subject-specific items.

   A GraphQL query that picks the portion of the data needed for the UI makes perfect sense to receive all data in a single request. It provides excellent concern separation: the client is aware of the data needs, and the server is aware of the data structure and understands how to retrieve data from a data source (e.g., database, microservice, third-party API).

2. No overfetching or under etching

   One of the best things about GraphQL is that it solves the problem of over-fetching and under-fetching.

   Overfetching happens when your app asks for more data than it needs, while under-fetching happens when it asks for less than it needs. Both are bad because they make your app slower to load and use.

   In GraphQL, you define exactly what data you need in one place – a single endpoint – and then you can fetch that data using any number of different clients (e.g., React Native apps, mobile web browsers, etc.). This means that if a client doesn’t need a particular field, they won’t have to waste time downloading it.

3. API evolution

   When an API changes, developers must continue using the previous version while switching to the new one. Therefore, offering several API versions is usual with REST. However, by deprecating APIs at the field level, GraphQL does away with the necessity for versioning.

   Aging fields can later be deleted from the schema without affecting the current queries. By establishing a consistent API throughout the entire application that is not constrained by a particular storage engine, GraphQL makes this possible.

   By employing a single, changing version, GraphQL APIs enable servers to write simpler, easier-to-maintain code while providing apps with continuous access to new capabilities.

4. Detailed error messages

   In REST, we only look up a response’s status in the HTTP headers so that we can figure out the problem and find a solution to fix it. On the other hand, if a problem arises when processing a GraphQL query, the backend will give a detailed error message that lists all the resolvers and refers to the specific query component at fault.

   There is no set format for GraphQL error messages, so you can use a stack trace, an application-specific error code, or just plain text.

5. Versioning

   There are no API versions in GraphQL like there formerly were with REST. Multiple versions of an API are standard in REST since the resources, or their structure may change over time (e.g., api.domain.com/v1/, api.domain.com/v2/). Detaching the API in GraphQL down to the field level is possible.

   As a result, when a client queries a deprecated field, a deprecation notice is displayed. The deprecated field may eventually be deleted from the schema if a few customers are still using it. This enables GraphQL API evolution over time without the requirement for
   versioning.

6. Keeping up with modern trends

   GraphQL supports modern developments in the development of applications. Depending on the data, you might have one backend application but several clients on the web, phones, and smartwatches.

   Without a unique API for every client, GraphQL can be used to connect both worlds while also fulfilling the needs of each client application, including those related to network consumption, nested relationships between data, and requests for only the necessary information.

   On the server side, there may be a single backend and a number of micro-services that each provides a different set of functionality. The ability to combine all functionalities into a single GraphQL schema, known as “stitching,” is used in this instance to design the ideal application.

7. Creating multiple schemas out of one

   For your backend, consider a micro-services architecture where each micro-service manages the business logic and data for a particular domain. Each microservice in this scenario is free to build its GraphQL schema, which is then combined using schema stitching into a single resource the client may access.

   One GraphQL API gateway consolidates all schemas into a single global schema, and each microservice can have its GraphQL endpoint.

Disadvantages of GraphQL

1. Query complexity

   It’s a common misconception that GraphQL can act as a server-side database replacement when it’s a query language. When a query must be resolved with information on the server, a GraphQL-independent implementation often makes a database call. Regarding it, GraphQL is neutral. Additionally, when you need to access many fields (authors, articles, and comments) in a single query, GraphQL does not eliminate performance constraints.

   There are various resources and fields that you must obtain from a data source, regardless of whether the request was made using GraphQL or a RESTful architecture. Because of this, issues develop when a client makes too many nested field requests.

   There must be a mechanism to stop inefficient requests from the other side because front-end developers are not always aware of the work a server-side application must do to retrieve data. Such mechanisms include maximum query depths, query complexity weighting, avoiding recursion, or persistent queries.

2. Rate limiting

   Rate limiting is another difficulty. While it is easier to say in REST, “we allow only so many resource requests in a day,” it becomes more challenging to say the same thing about GraphQL operations because they can range from inexpensive to expensive.

   That’s where businesses with open-source GraphQL APIs develop their unique rate limitation formulas, which frequently come down to the maximum query depths and query complexity factors indicated above.

3. Caching

   It is more difficult to construct a simple cache using GraphQL than it is to do so using REST. Because resources via REST are accessible via URLs, you can cache data at the resource level, as the URL serves as an identifier. This becomes more complicated in GraphQL because each query can be unique even though they all act on the same item.

   In one inquiry, you may only ask for the author’s name; in the next, you may only ask for the author’s email address. In that case, a more precise field-level cache is required, which can be challenging to build. However, the majority of GraphQL-based libraries come with built-in caching features.

4. Query failure response

   The fact that GraphQL queries always return an HTTP status code of 200 regardless of whether they were successful or not is another drawback of the language.

   In the event that your query is unsuccessful, a top-level error key with related error messages and stack traces will be present in the response JSON. This can make managing errors much more challenging and add complexity to processes like monitoring.

When to Use GraphQL

A backend development partner with the priority of integrating newer technology will be more likely to use GraphQL. However, it may not be right for every application.

Here are some of the situations where I’ve seen GraphQL used successfully:

• If your app relies heavily on data, then GraphQL can be a great way to manage that data.
• Another factor to consider is the type of data you’re dealing with. GraphQL is especially well-suited for apps that require handling complex, nested data.
• Finally, you should consider whether you need a flexible API. GraphQL’s schema-based approach makes it easy to change your API without breaking existing code.

Conclusion:

Overall, GraphQL is a promising solution for helping developers fulfil their needs in complex applications. It is important to remember that it is still young, but evolving quickly and becoming more popular daily.

If you require a web development agency in India, then you can avail of the services from SolGuruz. We have a team of highly skilled and experienced GraphQL experts who can create amazing websites and applications. Our top GraphQL developers use the latest technologies and follow the latest trends to create cutting-edge websites and apps.

FAQs

What are the benefits of GraphQL?

There are many benefits to using GraphQL over other traditional APIs. GraphQL provides a more efficient way to fetch data from your server and allows you to specify exactly what data you need. This means that you can avoid making unnecessary requests and be sure that you’re always getting the data you need.

What problems does GraphQL solve?

There are many different problems that GraphQL can help to solve. For example, GraphQL can help improve an API’s performance by allowing clients to request only the data they need. GraphQL can also help make an API more flexible and easier to use by allowing clients to request data in various ways. In addition, GraphQL can help reduce the amount of code that needs to be written by a web development agency when building an API and make it easier to maintain and update an API over time.

What are the limitations of GraphQL?

There are a few potential limitations of GraphQL to be aware of. Firstly, GraphQL can be quite complex, especially compared to API options like REST. Another potential limitation is that GraphQL can be quite slow compared to other API options which a top backend development company may find challenging. Finally, GraphQL is not yet as widely adopted as other API options, so there is a lack of tooling and community support compared to other options.

Does GraphQL replace REST?

There’s no simple answer to this question. It depends on several factors, including the specific needs of your project and the capabilities of the GraphQL and REST APIs. In general, however, it’s fair to say that GraphQL can provide many of the same benefits as REST but with some significant advantages.

Is GraphQL a database language like SQL?

No, GraphQL is not a database language like SQL. GraphQL is a client-server specification that is data source agnostic, meaning it can be used to communicate with different types of data sources. SQL, on the other hand, is specific to only one type of data source.

How does versioning work in GraphQL?

Versioning in GraphQL is a way of keeping your API updated without breaking existing clients. When you change your API, you can specify a new version number. Clients that specify this version number in their requests will get the updated API. Other clients will continue to get the old API.

Can GraphQL work with any database?

Yes, GraphQL can work with any database. It can work with any data source that can be queried. This makes it an ideal tool for GraphQL experts to create APIs that work with various data sources. For example, you could use GraphQL to create an API that works with a relational database, a NoSQL database, or even a simple file system.