firebase-data-connect
Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.
What this skill does
# 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
```text
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:
1. **Review GraphQL Schema**: Both user-defined and generated extensions (in `.dataconnect/schema/main/`).
2. **Validate Operations**: Run `npx -y firebase-tools@latest dataconnect:compile` against 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](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](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](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](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](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`:
```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"
```
Generate SDKs:
```bash
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](reference/sdk_web.md)
* **Android (Kotlin)**: [reference/sdk_android.md](reference/sdk_android.md)
* **iOS (Swift)**: [reference/sdk_ios.md](reference/sdk_ios.md)
* **Admin (Node.js)**: [reference/sdk_admin_node.md](reference/sdk_admin_node.md)
* **Flutter (Dart)**: [reference/sdk_flutter.md](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](reference/schema.md) | `@table`, `@unique`, `@index`, Relations |
| **Vector Search** | [reference/search.md](reference/search.md) | `Vector`, `@col(dataType: "vector")`, embeddings |
| **Full-Text Search** | [reference/search.md](reference/search.md) | `@searchable`, `movies_search` |
| **Upserting Data** | [reference/operations.md](reference/operations.md) | `_upsert` mutations |
| **Complex Filters** | [reference/operations.md](reference/operations.md) | `_or`, `_and`, `_not`, `eq`, `contains` |
| **Transactions** | [reference/operations.md](reference/operations.md) | `@transaction`, `response` binding |
| **Environment Config** | [reference/config.md](reference/config.md) | `dataconnect.yaml`, `connector.yaml` |
| **Realtime Subscriptions** | [reference/realtime.md](reference/realtime.md) | `@refresh`, `subscribe()`, auto-refresh |
| **Cloud Functions Integration** | [reference/cloud_functions.md](reference/cloud_functions.md) | `onMutationExecuted`, triggering events |
| **Data Seeding & Migrations** | [reference/data_seeding.md](reference/data_seeding.md) | `seed_data.gql`, `_insertMany`, Admin SDK bulk |
| **Starter Templates** | [templates.md](templates.md) | CRUD, user-owned resources, many-to-many, SDK init |
---
## Deployment & CLI
> **Read [reference/config.md](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
1. Understand the app idea. Ask clarification questions if unclear.
2. Run `npx -y firebase-tools@latest init dataconnect`.
3. Validate that the app template and generated SDK are setup.
### How to build apps using SQL Connect locally
1. Start the emulator: `npx -y firebase-tools@latest emulators:start --only dataconnect`.
2. Write schema and operations.
3. Seed local test data into `seed_data.gql`. Read [reference/data_seeding.md](reference/data_seeding.md#local-prototyping-data-seeding).
4. Run `npx -y firebase-tools@latest dataconnect:compile` or `npx -y firebase-tools@latest dataconnect:sdk:generate` to
validate them.
5. Use the operations in your app and build it.
### How to deploy SQL Connect to Cloud SQL
1. Run `npx -y firebase-tools@latest deploy --only dataconnect`.
## Examples
For complete, working code examples of schemas and operations, see
**[examples.md](examples.md)**.
For ready-to-use starter templates (CRUD, user-owned resources, many-to-many, YAML configs, SDK init), see **[templates.md](templates.md)**.
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