GraphQL schema basics
Your GraphQL server uses a schema to describe the shape of your available data. This schema defines a hierarchy of types with fields that are populated from your back-end data stores. The schema also specifies exactly which queries and mutations are available for clients to execute.
This article describes the fundamental building blocks of a schema and how to create one for your GraphQL server.
The schema definition language
The GraphQL specification defines a human-readable schema definition language (or SDL) that you use to define your schema and store it as a string.
Here's a short example schema that defines two object types: Book
and Author
:
1type Book {
2 title: String
3 author: Author
4}
5
6type Author {
7 name: String
8 books: [Book]
9}
A schema defines a collection of types and the relationships between those types. In the example schema above, a Book
can have an associated author
, and an Author
can have a list of books
.
Because these relationships are defined in a unified schema, client developers can see exactly what data is available and then request a specific subset of that data with a single optimized query.
Note that the schema is not responsible for defining where data comes from or how it's stored. It is entirely implementation-agnostic.
Field definitions
Most of the schema types you define have one or more fields:
1# This Book type has two fields: title and author
2type Book {
3 title: String # returns a String
4 author: Author # returns an Author
5}
Each field returns data of the type specified. A field's return type can be a scalar, object, enum, union, or interface (all described below).
List fields
A field can return a list containing items of a particular type. You indicate list fields with square brackets []
, like so:
1type Author {
2 name: String
3 books: [Book] # A list of Books
4}
Field nullability
By default, it's valid for any field in your schema to return null
instead of its specified type. You can require that a particular field doesn't return null
with an exclamation mark !
, like so:
1type Author {
2 name: String! # Can't return null
3 books: [Book]
4}
These fields are non-nullable. If your server attempts to return null
for a non-nullable field, an error is thrown.
Nullability and lists
With a list field, an exclamation mark !
can appear in any combination of two locations:
1type Author {
2 books: [Book!]! # This list can't be null AND its list *items* can't be null
3}
If
!
appears inside the square brackets, the returned list can't include items that arenull
.If
!
appears outside the square brackets, the list itself can't benull
.In any case, it's valid for a list field to return an empty list.
Supported types
Every type definition in a GraphQL schema belongs to one of the following categories:
This includes the three special root operation types:
Query
,Mutation
, andSubscription
.
Each of these is described below.
Scalar types
Scalar types are similar to primitive types in your favorite programming language. They always resolve to concrete data.
GraphQL's default scalar types are:
Int
: A signed 32‐bit integerFloat
: A signed double-precision floating-point valueString
: A UTF‐8 character sequenceBoolean
:true
orfalse
ID
(serialized as aString
): A unique identifier that's often used to refetch an object or as the key for a cache. Although it's serialized as aString
, anID
is not intended to be human‐readable.
These primitive types cover the majority of use cases. For more specific use cases, you can create custom scalar types.
Object types
Most of the types you define in a GraphQL schema are object types. An object type contains a collection of fields, each of which has its own type.
Two object types can include each other as fields, as is the case in our example schema from earlier:
1type Book {
2 title: String
3 author: Author
4}
5
6type Author {
7 name: String
8 books: [Book]
9}
The __typename
field
Every object type in your schema automatically has a field named __typename
(you don't need to define it). The __typename
field returns the object type's name as a String
(e.g., Book
or Author
).
GraphQL clients use an object's __typename
for many purposes, such as to determine which type was returned by a field that can return multiple types (i.e., a union or interface). Apollo Client relies on __typename
when caching results, so it automatically includes __typename
in every object of every query.
Because __typename
is always present, this is a valid query for any GraphQL server:
1query UniversalQuery {
2 __typename
3}
The Query
type
The Query
type is a special object type that defines all of the top-level entry points for queries that clients execute against your server.
Each field of the Query
type defines the name and return type of a different entry point. The Query
type for our example schema might resemble the following:
1type Query {
2 books: [Book]
3 authors: [Author]
4}
This Query
type defines two fields: books
and authors
. Each field returns a list of the corresponding type.
With a REST-based API, books and authors would probably be returned by different endpoints (e.g., /api/books
and /api/authors
). The flexibility of GraphQL enables clients to query both resources with a single request.
Structuring a query
When your clients build queries to execute against your graph, those queries match the shape of the object types you define in your schema.
Based on our example schema so far, a client could execute the following query, which requests both a list of all book titles and a list of all author names:
1query GetBooksAndAuthors {
2 books {
3 title
4 }
5
6 authors {
7 name
8 }
9}
Our server would then respond to the query with results that match the query's structure, like so:
1{
2 "data": {
3 "books": [
4 {
5 "title": "City of Glass"
6 },
7 ...
8 ],
9 "authors": [
10 {
11 "name": "Paul Auster"
12 },
13 ...
14 ]
15 }
16}
Although it might be useful in some cases to fetch these two separate lists, a client would probably prefer to fetch a single list of books, where each book's author is included in the result.
Because our schema's Book
type has an author
field of type Author
, a client could instead structure their query like so:
1query GetBooks {
2 books {
3 title
4 author {
5 name
6 }
7 }
8}
And once again, our server would respond with results that match the query's structure:
1{
2 "data": {
3 "books": [
4 {
5 "title": "City of Glass",
6 "author": {
7 "name": "Paul Auster"
8 }
9 },
10 ...
11 ]
12 }
13}
The Mutation
type
The Mutation
type is similar in structure and purpose to the Query
type. Whereas the Query
type defines entry points for read operations, the Mutation
type defines entry points for write operations.
Each field of the Mutation
type defines the signature and return type of a different entry point. The Mutation
type for our example schema might resemble the following:
1type Mutation {
2 addBook(title: String, author: String): Book
3}
This Mutation
type defines a single available mutation, addBook
. The mutation accepts two arguments (title
and author
) and returns a newly created Book
object. As you'd expect, this Book
object conforms to the structure that we defined in our schema.
Structuring a mutation
Like queries, mutations match the structure of your schema's type definitions. The following mutation creates a new Book
and requests certain fields of the created object as a return value:
1mutation CreateBook {
2 addBook(title: "Fox in Socks", author: "Dr. Seuss") {
3 title
4 author {
5 name
6 }
7 }
8}
As with queries, our server would respond to this mutation with a result that matches the mutation's structure, like so:
1{
2 "data": {
3 "addBook": {
4 "title": "Fox in Socks",
5 "author": {
6 "name": "Dr. Seuss"
7 }
8 }
9 }
10}
A single mutation operation can include multiple top-level fields of the Mutation
type. This usually means that the operation will execute multiple back-end writes (at least one for each field). To prevent race conditions, top-level Mutation
fields are resolved serially in the order they're listed (all other fields can be resolved in parallel).
Learn more about designing mutations
The Subscription
type
See Subscriptions.
Input types
Input types are special object types that allow you to provide hierarchical data as arguments to fields (as opposed to providing only flat scalar arguments).
An input type's definition is similar to an object type's, but it uses the input
keyword:
1input BlogPostContent {
2 title: String
3 body: String
4}
Each field of an input type can be only a scalar, an enum, or another input type:
1input BlogPostContent {
2 title: String
3 body: String
4 media: [MediaDetails!]
5}
6
7input MediaDetails {
8 format: MediaFormat!
9 url: String!
10}
11
12enum MediaFormat {
13 IMAGE
14 VIDEO
15}
After you define an input type, any number of different object fields can accept that type as an argument:
1type Mutation {
2 createBlogPost(content: BlogPostContent!): Post
3 updateBlogPost(id: ID!, content: BlogPostContent!): Post
4}
Input types can sometimes be useful when multiple operations require the exact same set of information, but you should reuse them sparingly. Operations might eventually diverge in their sets of required arguments.
Take care if using the same input type for fields of both
Query
andMutation
. In many cases, arguments that are required for a mutation are optional for a corresponding query. You might want to create separate input types for each operation type.
Enum types
An enum is similar to a scalar type, but its legal values are defined in the schema. Here's an example definition:
1enum AllowedColor {
2 RED
3 GREEN
4 BLUE
5}
Enums are most useful in situations where the user must pick from a prescribed list of options. As an additional benefit, enum values autocomplete in tools like the Apollo Studio Explorer.
An enum can appear anywhere a scalar is valid (including as a field argument), because they serialize as strings:
1type Query {
2 favoriteColor: AllowedColor # enum return value
3 avatar(borderColor: AllowedColor): String # enum argument
4}
A query might then look like this:
1query GetAvatar {
2 avatar(borderColor: RED)
3}
Internal values (advanced)
Sometimes, a backend forces a different value for an enum internally than in the public API. You can set each enum value's corresponding internal value in the resolver map you provide to Apollo Server.
This feature usually isn't required unless another library in your application expects enum values in a different form.
The following example uses color hex codes for each AllowedColor
's internal value:
1const resolvers = {
2 AllowedColor: {
3 RED: '#f00',
4 GREEN: '#0f0',
5 BLUE: '#00f',
6 }
7 // ...other resolver definitions...
8};
These internal values don't change the public API at all. Apollo Server resolvers accept these values instead of the schema values, as shown:
1const resolvers = {
2 AllowedColor: {
3 RED: '#f00',
4 GREEN: '#0f0',
5 BLUE: '#00f',
6 },
7 Query: {
8 favoriteColor: () => '#f00',
9 avatar: (parent, args) => {
10 // args.borderColor is '#f00', '#0f0', or '#00f'
11 },
12 }
13};
Union and interface types
Growing with a schema
As your organization grows and evolves, your graph grows and evolves with it. New products and features introduce new schema types and fields. To track these changes over time, you should maintain your schema's definition in version control.
Most additive changes to a schema are safe and backward compatible. However, changes that remove or alter existing behavior might be breaking changes for one or more of your existing clients. All of the following schema changes are potentially breaking changes:
Removing a type or field
Renaming a type or field
Adding nullability to a field
Removing a field's arguments
A graph management tool such as Apollo Studio helps you understand whether a potential schema change will impact any of your active clients. Studio also provides field-level performance metrics, schema history tracking, and advanced security via operation safelisting.
Descriptions (docstrings)
GraphQL's schema definition language (SDL) supports Markdown-enabled documentation strings, called descriptions. These help consumers of your graph discover fields and learn how to use them.
The following snippet shows how to use both single-line string literals and multi-line blocks:
1"Description for the type"
2type MyObjectType {
3 """
4 Description for field
5 Supports **multi-line** description for your [API](http://example.com)!
6 """
7 myField: String!
8
9 otherField(
10 "Description for argument"
11 arg: Int
12 )
13}
A well documented schema helps provide an enhanced development experience, because GraphQL development tools (such as Apollo Explorer) auto-complete field names along with descriptions when they're provided. Furthermore, Apollo Studio displays descriptions alongside field usage and performance details when using its metrics reporting and client awareness features.
Naming conventions
The GraphQL specification is flexible and doesn't impose specific naming guidelines. However, it's helpful to establish a set of conventions to ensure consistency across your organization. We recommend the following:
Field names should use
camelCase