Firebase Data Connect
Databases & backend175.5K installs
What it does
Firebase SQL Connect is a relational database service using Cloud SQL for PostgreSQL with GraphQL schema, auto-generated queries/mutations, and type-safe SDKs.
Install
npx skills add https://github.com/firebase/agent-skills --skill firebase-data-connectWebsite
www.skills.sh/firebase/agent-skills/firebase-data-connectDetails
From the skill’s SKILL.md or README, by its authors. View the original
Firebase SQL Connect
Firebase SQL Connect is a relational database service using Cloud SQL for PostgreSQL with GraphQL schema, auto-generated queries/mutations, and type-safe SDKs.
> [!NOTE] Product Rename: Firebase Data Connect was renamed to Firebase SQL Connect. All instructions, references, and examples in this skill repository referring to Data Connect or Firebase Data Connect apply to SQL Connect and Firebase SQL Connect as well.
Project Structure
dataconnect/
├── dataconnect.yaml # Service configuration
├── seed_data.gql # LOCAL ONLY — prototype/test data
├── schema/
│ └── schema.gql # Data model (types with @table)
└── connector/
├── connector.yaml # Connector config + SDK generation
├── queries.gql # Queries
└── mutations.gql # Mutations
Key Tools for Validation
Rely on these two mechanisms to ensure project correctness:
- Review GraphQL Schema: Both user-defined and generated extensions (in
.dataconnect/schema/main/).
- Validate Operations: Run
npx -y firebase-tools@latest dataconnect:compileagainst the schema.
Operation Strategies: GraphQL vs. Native SQL
Always default to Native GraphQL. Native SQL lacks type safety and bypasses schema-enforced structures. Only use Native SQL when the user explicitly requests it or when the task requires advanced database features.
| Strategy | When to use | Implementation |
|---|---|---|
| Native GraphQL (Default) | Almost all use cases. Standard CRUD, basic filtering/sorting, simple relational joins. Requires full type safety. | Auto-generated fields (movie_insert, movies). Strong typing and schema enforcement. |
| Native SQL (Advanced) | PostgreSQL extensions (e.g., PostGIS), window functions (RANK()), complex aggregations, or highly tuned sub-queries. | Raw SQL string literals via _select, _execute, etc. Requires strict positional parameters ($1). No type safety. |
Development Workflow
Follow this strict workflow to build your application. You must read the linked reference files for each step to understand the syntax and available features.
1. Define Data Model (schema/schema.gql)
Define your GraphQL types, tables, and relationships (which map to a Postgres schema).
> Read reference/schema.md for: - @table, @col, @default - Relationships (@ref, one-to-many, many-to-many) - Data types (UUID, Vector, JSON, etc.)
2. Define Authorized Operations (connector/queries.gql, connector/mutations.gql)
Write the queries and mutations your client will use, including authorization logic. SQL Connect is secure by default.
> Read reference/operations.md for: - Queries: Filtering (where), Ordering (orderBy), Pagination (limit/offset). - Mutations: Create (_insert), Update (_update), Delete (_delete). - Upserts: Use _upsert to insert or update records (CRITICAL for user profiles). - Transactions: Use @transaction for multi-step atomic operations. Use _expr: "response.<prevStep>" to pass data between steps. Read reference/security.md for authorization: - @auth(level: ...) for PUBLIC, USER, or NO_ACCESS. - @check and @redact for row-level security and validation. Read reference/realtime.md for real-time subscriptions: - @refresh directive for time-based polling and event-driven updates. - CEL conditions to scope refresh triggers precisely. Read reference/native_sql.md for Native SQL operations: - Embedding raw SQL with _select, _selectFirst, _execute - Strict rules for positional parameters ($1, $2), quoting, and CTEs - Advanced PostgreSQL features (PostGIS, Window Functions)
3. Use type-safe SDK in your apps
Generate type-safe code for your client platform.
Configure SDK generation in connector.yaml:
connectorId: my-connector
generate:
javascriptSdk:
outputDir: "../web-app/src/lib/dataconnect"
package: "@movie-app/dataconnect"
kotlinSdk:
outputDir: "../android-app/app/src/main/kotlin/com/example/dataconnect"
package: "com.example.dataconnect"
swiftSdk:
outputDir: "../ios-app/DataConnect"
package: "DataConnectGenerated"
Generate SDKs:
npx -y firebase-tools@latest dataconnect:sdk:generate
For platform-specific instructions on how to use the generated SDKs, read:
- Web (TypeScript): reference/sdk_web.md
- Android (Kotlin): reference/sdk_android.md
- iOS (Swift): reference/sdk_ios.md
- Admin (Node.js): reference/sdk_admin_node.md
- Flutter (Dart): reference/sdk_flutter.md
Feature Capability Map
If you need to implement a specific feature, consult the mapped reference file:
| Feature | Reference File | Key Concepts |
|---|---|---|
| Data Modeling | reference/schema.md | @table, @unique, @index, Relations |
| Vector Search | reference/search.md | Vector, @col(dataType: "vector"), embeddings |
| Full-Text Search | reference/search.md | @searchable, movies_search |
| Upserting Data | reference/operations.md | _upsert mutations |
| Complex Filters | reference/operations.md | _or, _and, _not, eq, contains |
| Transactions | reference/operations.md | @transaction, response binding |
| Environment Config | reference/config.md | dataconnect.yaml, connector.yaml |
| Realtime Subscriptions | reference/realtime.md | @refresh, subscribe(), auto-refresh |
| Cloud Functions Integration | reference/cloud_functions.md | onMutationExecuted, triggering events |
| Data Seeding & Migrations | reference/data_seeding.md | seed_data.gql, _insertMany, Admin SDK bulk |
| Starter Templates | templates.md | CRUD, user-owned resources, many-to-many, SDK init |
Deployment & CLI
> Read reference/config.md for deep dive on configuration.
Follow these patterns based on your current task:
How to initialize SQL Connect in a Firebase project
- Understand the app idea. Ask clarification questions if unclear.
- Run
npx -y firebase-tools@latest init dataconnect.
- Validate that the app template and generated SDK are setup.
How to build apps using SQL Connect locally
- Start the emulator:
npx -y firebase-tools@latest emulators:start --only dataconnect.
- Write schema and operations.
- Seed local test data into
seed_data.gql. Read reference/data_seeding.md.
- Run
npx -y firebase-tools@latest dataconnect:compileornpx -y firebase-tools@latest dataconnect:sdk:generateto validate them.
- Use the operations in your app and build it.
How to deploy SQL Connect to Cloud SQL
- Run
npx -y firebase-tools@latest deploy --only dataconnect.
Examples
For complete, working code examples of schemas and operations, see examples.md.
For ready-to-use starter templates (CRUD, user-owned resources, many-to-many, YAML configs, SDK init), see templates.md.
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