GraphQL API Versioning Approaches

About

Unlike REST, GraphQL discourages explicit version numbers in the API endpoint. Instead, the philosophy is to evolve the schema incrementally while maintaining backward compatibility. In GraphQL, the endpoint typically remains fixed (e.g., /graphql), and all version control is managed within the schema and resolver logic.

The reasoning:

• GraphQL clients explicitly request only the fields they need.

• Adding new fields or types is non-breaking.

• Deprecated fields can be gradually phased out without breaking existing clients.

However, schema evolution must be managed carefully, and there are still situations where more drastic versioning approaches are needed.

Approaches

1. Schema Evolution without Endpoint Changes (Preferred)

Example:

# Existing field
type Customer {
  id: ID!
  name: String!
}

# Adding new field (non-breaking)
type Customer {
  id: ID!
  name: String!
  email: String # newly added
}

How It Works:

• Fields are added in a backward-compatible way.

• No fields or types are removed abruptly.

• Deprecated fields remain available until safe removal.

Advantages:

• Single endpoint — no proliferation of /v1, /v2 URLs.

• Client-driven upgrades — clients can adopt new fields at their own pace.

• Reduced operational complexity.

Disadvantages:

• Requires strict discipline to avoid breaking changes.

• Removal of deprecated fields must be coordinated with all client teams.

Operational Notes:

• Use @deprecated(reason: "...") annotations for old fields.

• Establish deprecation timelines and communicate via release notes.

2. Field Deprecation and Sunset Policy

Example:

type Customer {
  id: ID!
  fullName: String! @deprecated(reason: "Use 'firstName' and 'lastName'")
  firstName: String!
  lastName: String!
}

How It Works:

• Fields that should not be used are marked with @deprecated.

• Clients are expected to stop querying these fields before removal.

• Deprecation reason is visible in schema introspection tools (e.g., GraphiQL).

Advantages:

• In-schema communication — Developers discover deprecations directly via schema inspection.

• Smooth migration path for clients.

Disadvantages:

• Clients may ignore deprecation notices.

• No enforcement until the field is actually removed.

Governance Notes:

• Combine deprecation annotations with external announcements.

• Define minimum deprecation periods (e.g., 6 months) before removal.

3. Separate Schemas for Major Breaks

While GraphQL prefers evolving one schema, some scenarios justify separate schema versions:

• Major architectural changes (e.g., switching from relational DB to event-sourced model).

• Complete redesign of resource structures.

• Compliance or security-driven changes requiring a clean slate.

Approaches:

• Endpoint separation:

  POST /graphql/v1
  POST /graphql/v2

• Schema separation inside the same endpoint:

  • Namespacing types (V2Customer, V2Order).

  • Using directives to separate execution paths.

Advantages:

• Allows radical redesigns without impacting old clients.

• Enables running parallel resolvers.

Disadvantages:

• Defeats some of GraphQL’s single-source-of-truth appeal.

• Higher maintenance cost — two schemas must be updated independently.

4. Experimental Feature Flags

Sometimes new fields or types are introduced only for beta testers:

• Implement server-side feature toggles.

• Hide or expose fields based on user roles or API key metadata.

Advantages:

• Enables incremental rollout of risky features.

• Allows internal testing before public release.

Disadvantages:

• Can complicate schema introspection results.

• Risk of inconsistent API experiences if flags are not aligned across environments.

Change Monitoring and Governance

To manage GraphQL versioning effectively:

1. Schema Change Tracking — Use tools like Apollo Studio or GraphQL Inspector to detect breaking changes before deployment.

2. Backward Compatibility Contracts — Define what counts as a breaking change (e.g., removing a field, changing a field’s type, making a nullable field non-nullable).

3. Automated Schema Diffing — Run CI/CD jobs that compare the current schema against the last released schema.

4. Consumer-Driven Contracts (CDC) — Align with client teams before making changes.

When Explicit Versioning is Unavoidable ?

While GraphQL promotes schema evolution over explicit version numbers, explicit endpoint versioning may be required when:

• Breaking business model changes make old queries meaningless.

• API governance rules mandate freezing old schemas for regulatory reasons.

• Contractual obligations require keeping an untouched "v1" for certain partners.