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Why adopt GraphQL?

GraphQL and Apollo help you ship features faster


Managing data in modern applications is challenging. Most applications require:

  • Distinct frontend clients for multiple platforms (web, iOS, etc.), each with different data requirements
  • A backend that serves data to clients from multiple sources (Postgres, Redis, etc.)
  • Complex state and cache management for both the frontend and the backend

By adopting and Apollo, you can reduce these challenges considerably. GraphQL's declarative model helps you create a consistent, predictable API you can use across all your clients. As you add, remove, and migrate backend data stores, that API doesn't change from the client's perspective.

Even with many other advantages, 's single greatest benefit is the developer experience it provides. It's straightforward to add new types and to your API, and similarly straightforward for your clients to begin using those fields. This helps you design, develop, and deploy features quickly.

Combined with Apollo open-source libraries, complex considerations like caching, data , and optimistic UI rendering become straightforward as well.

GraphQL provides declarative, efficient data fetching

's declarative approach to data fetching provides significant performance and quality-of-life improvements over a REST API.

Consider a webpage that displays a list of adorable pets that are available for adoption at local animal shelters. 🐶

Using REST

Using REST, the page might need to:

  1. GET a list of shelters and their corresponding pet_ids from the /api/shelters endpoint
  2. GET each individual pet's details (name, photo URL, etc.) with a separate request to /api/pets/PET_ID

This solution requires multiple dependent network requests, which can result in slower page loads and additional battery consumption on mobile devices. This logic is also difficult to reuse on other pages that display slightly different data.

Using GraphQL

Using , the page can obtain all this data with a single to a single endpoint. That query looks like this:

query GetPetsByShelter {
shelters {
name
pets {
name
photoURL
}
}
}

This describes the shape of the data we want to receive from the . The server takes care of combining and filtering backend data to return exactly what we ask for. This keeps payload sizes small, especially compared to a REST endpoint that might return hundreds of unnecessary .

To execute a like the one above, the page uses a such as

, with code that resembles the following (in the case of a React app):

mainpage.jsx
// Define the query
const GET_PETS_BY_SHELTER = gql`
query GetPetsByShelter {
shelters {
name
pets {
name
photoURL
}
}
}
`;
function MainPage() {
// Execute the query within the component that uses its result
const { loading, error, data } = useQuery(GET_PETS_BY_SHELTER);
if (error) return <Error />;
if (loading || !data) return <Fetching />;
// Populate the component using the query's result
return <PetList shelters={data.shelters} />;
}

's useQuery hook takes care of the request lifecycle from start to finish, including tracking loading and error states for you. There's no middleware to set up or boilerplate to write before making your first request. All you need to do is describe the data your component needs and let do the heavy lifting. 💪

GraphQL enables powerful tooling

Thanks to 's

and built-in support for
introspection
, developer tools for are extremely powerful. These tools let you do things like:

  • Explore the full structure of a schema, complete with s
  • Compose new with live validation and autocomplete
  • Register your schema with a management service that tracks and checks changes

What is Apollo GraphOS?

Apollo provides a cloud-hosted collection of tools that help you build your , measure its performance, and grow it safely. These tools are together known as

.

After registering your schema with , you can use the to inspect all its types and . You can also build and run queries against your running server:

Studio Explorer tab

Apollo Client DevTools

The DevTools extension for

and
Firefox
enables you to inspect your cache, track active queries, and view . It also includes an embedded version of the Explorer, which helps you test queries while you're working on frontend code.

Apollo DevTools

GraphQL is production-ready

's adoption has risen steadily since Facebook published the original

in 2015. For more and more organizations, the benefits of have taken it from a curious engineer's hack-week experiment to the heart of the enterprise data layer.

scales with the requirements of even the largest organizations, largely because of its

and its compatibility with a
federated architecture
.

In a federated architecture, also known as a supergraph, a single is split across multiple backend services. Each team in an organization can then own exactly the services (and the corresponding parts of the schema) that they should.

Organizations using GraphQL

Here are a few blog posts from organizations that have benefited from adopting in their production environment:

GraphQL trade-offs

When deciding whether to adopt a technology, it's just as important to understand the technology's limitations as it is to understand its benefits.

Consider the following trade-offs when using :

Change management

introduces a new conceptual model for representing and interacting with data. An organization that's comfortable with this model can design, implement, and ship features quickly. However, the process of becoming comfortable with this model takes time.

  • Frontend developers must come up to speed with a new API for fetching and manipulating data.
  • Backend developers must come up to speed with how to handle incoming requests from the frontend.
  • Developers across the organization must collaborate on a single, product-driven and appoint individuals as the official maintainers of that schema.

The Apollo

,
blog
, and
community forum
are all here to help your organization adopt and take full advantage of it.

Potential for slow operations

Your

defines which types and your clients can . Your 's
resolvers
define how those types and are populated from your data stores.

Depending on your schema and your definitions, your server might inadvertently support that execute slowly, or even max out your server's resources.

Consequently, it's important to design your schema such that it supports the your clients need, without supporting unnecessary operations that affect performance. It's also helpful to set up

for your , enabling you to identify and improve slow .

.

Incompatibility with web browser caching

Although

provides powerful client-side
caching features
, those features often require some configuration to get the most out of them. The automatic caching provided by your web browser does not interact well with .

Web browsers cache fetched data according to its URL. With , you fetch all data from the same URL (the URL of your ). Consequently, you can't rely on the cached value for this URL.

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