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driver for Databricks Lakebase Autoscaling with automatic OAuth token refresh","maintainers":[],"readme":"# @databricks/lakebase\n\nPostgreSQL driver for Databricks Lakebase Autoscaling with automatic OAuth token refresh.\n\n## Overview\n\n`@databricks/lakebase` provides a drop-in replacement for the standard `pg` connection pool that automatically handles OAuth authentication for Databricks Lakebase Autoscaling (OLTP) databases.\n\nIt:\n\n- Returns a standard `pg.Pool` - works with any PostgreSQL library or ORM\n- Automatically refreshes OAuth tokens (1-hour lifetime, with 2-minute buffer)\n- Caches tokens to minimize API calls\n- Zero configuration with environment variables\n- Optional OpenTelemetry instrumentation\n\n**NOTE:** This package is NOT compatible with the Databricks Lakebase Provisioned.\n\n## Installation\n\n```bash\nnpm install @databricks/lakebase\n```\n\n## Quick Start\n\n### Using Environment Variables\n\nSet the following environment variables:\n\n```bash\nexport PGHOST=your-lakebase-host.databricks.com\nexport PGDATABASE=your_database_name\nexport LAKEBASE_ENDPOINT=projects/6bef4151-4b5d-4147-b4d0-c2f4fd5b40db/branches/br-broad-pine-y12n6gnv/endpoints/ep-summer-frost-y131l3vx\nexport PGUSER=your_user # optionally, defaults to DATABRICKS_CLIENT_ID\nexport PGSSLMODE=require\n```\n\nTo find your `LAKEBASE_ENDPOINT`, run the Databricks CLI and use the `name` field from the output:\n\n```bash\ndatabricks postgres list-endpoints projects/{project-id}/branches/{branch-id}\n```\n\nYou can obtain the Project ID and Branch ID from the Lakebase Autoscaling UI, like the \"Branch Overview\" page. (Project list -> Project dashboard -> Branch overview). \n\nThen use the driver:\n\n```typescript\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\nconst pool = createLakebasePool();\nconst result = await pool.query(\"SELECT * FROM users\");\nconsole.log(result.rows);\n```\n\n### With Explicit Configuration\n\n```typescript\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\nconst pool = createLakebasePool({\n  host: \"your-lakebase-host.databricks.com\", // defaults to PGHOST environment variable\n  database: \"your_database_name\", // defaults to PGDATABASE environment variable\n  endpoint:\n    \"projects/6bef4151-4b5d-4147-b4d0-c2f4fd5b40db/branches/br-broad-pine-y12n6gnv/endpoints/ep-summer-frost-y131l3vx\", // defaults to LAKEBASE_ENDPOINT environment variable\n  user: \"user_id\", // Optional, defaults to PGUSER or DATABRICKS_CLIENT_ID\n  max: 10, // Connection pool size\n});\n```\n\n## Authentication\n\nThe driver supports Databricks authentication via:\n\n1. **Default auth chain** (`.databrickscfg`, environment variables)\n2. **OAuth tokens** (via Databricks SDK)\n3. **Native Postgres password authentication**\n\nSee [Databricks authentication docs](https://docs.databricks.com/en/dev-tools/auth/index.html) or [Lakebase Autoscaling authentication docs](https://docs.databricks.com/aws/en/oltp/projects/authentication#overview) for more information.\n\n## PostgreSQL Username Resolution\n\nThe driver resolves the PostgreSQL username (`user` configuration option) using the following priority order:\n\n1. `config.user` — explicit value passed to `createLakebasePool`\n2. `PGUSER` environment variable\n3. `DATABRICKS_CLIENT_ID` environment variable (service principals using OAuth M2M)\n\nIf none of these are set, the driver throws a `ConfigurationError`.\n\n### Automatic resolution via Workspace API\n\nFor human users authenticating with a PAT token or browser OAuth via `~/.databrickscfg`, none of the above are typically set. Use `getUsernameWithApiLookup` to automatically fetch the username from the Databricks workspace before creating the pool:\n\n```typescript\nimport { createLakebasePool, getUsernameWithApiLookup } from \"@databricks/lakebase\";\n\n// Tries config/env vars first, then falls back to currentUser.me() API call\nconst user = await getUsernameWithApiLookup();\n\nconst pool = createLakebasePool({ user });\n```\n\n`getUsernameWithApiLookup` extends the sync resolution above with a fourth step:\n\n4. `currentUser.me()` — fetches the current user's identity from the Databricks workspace API (works with PAT tokens and browser OAuth in `~/.databrickscfg`)\n\n> **Note:** `getUsernameWithApiLookup` makes a network call to the Databricks workspace API when the sync resolution steps (config, `PGUSER`, `DATABRICKS_CLIENT_ID`) all fail. Call it once during initialization, not on every request.\n\n## Configuration\n\n| Option                    | Environment Variable               | Description                             | Default                 |\n| ------------------------- | ---------------------------------- | --------------------------------------- | ----------------------- |\n| `host`                    | `PGHOST`                           | Lakebase host                           | _Required_              |\n| `database`                | `PGDATABASE`                       | Database name                           | _Required_              |\n| `endpoint`                | `LAKEBASE_ENDPOINT`                | Endpoint resource path                  | _Required_              |\n| `user`                    | `PGUSER` or `DATABRICKS_CLIENT_ID` | Username or service principal ID        | See [Username Resolution](#username-resolution)|\n| `port`                    | `PGPORT`                           | Port number                             | `5432`                  |\n| `sslMode`                 | `PGSSLMODE`                        | SSL mode                                | `require`               |\n| `max`                     | -                                  | Max pool connections                    | `10`                    |\n| `idleTimeoutMillis`       | -                                  | Idle connection timeout                 | `30000`                 |\n| `connectionTimeoutMillis` | -                                  | Connection timeout                      | `10000`                 |\n| `logger`                  | -                                  | Logger instance or config               | `{ error: true }`       |\n\n## Logging\n\nBy default, the driver logs errors only. You can configure logging in three ways:\n\n### 1. Config-Based Logger (Simple)\n\nEnable/disable specific log levels using boolean flags:\n\n```typescript\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\n// Development mode: enable debug and error logs\nconst pool = createLakebasePool({\n  logger: { debug: true, error: true },\n});\n\n// Production mode: errors only (same as default)\nconst pool = createLakebasePool({\n  logger: { error: true },\n});\n\n// Verbose mode: all logs enabled\nconst pool = createLakebasePool({\n  logger: { debug: true, info: true, warn: true, error: true },\n});\n\n// Silent mode: all logs disabled\nconst pool = createLakebasePool({\n  logger: { debug: false, info: false, warn: false, error: false },\n});\n```\n\n### 2. Custom Logger (Advanced)\n\nInject your own logger implementation for custom formatting or integrations:\n\n```typescript\nconst logger = {\n  debug: (msg: string, ...args: unknown[]) => console.debug(msg, ...args),\n  info: (msg: string, ...args: unknown[]) => console.log(msg, ...args),\n  warn: (msg: string, ...args: unknown[]) => console.warn(msg, ...args),\n  error: (msg: string, ...args: unknown[]) => console.error(msg, ...args),\n};\n\nconst pool = createLakebasePool({ logger });\n```\n\n### 3. Default Behavior\n\nIf no logger is provided, the driver defaults to error-only logging:\n\n```typescript\n// These are equivalent:\nconst pool1 = createLakebasePool();\nconst pool2 = createLakebasePool({ logger: { error: true } });\n```\n\nWhen used with AppKit, logging is automatically configured - see the [AppKit Integration](#appkit-integration) section.\n\n## ORM Examples\n\n### Drizzle ORM\n\n```typescript\nimport { drizzle } from \"drizzle-orm/node-postgres\";\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\nconst pool = createLakebasePool();\nconst db = drizzle(pool);\n\nconst users = await db.select().from(usersTable);\n```\n\n### Prisma\n\n```typescript\nimport { PrismaPg } from \"@prisma/adapter-pg\";\nimport { PrismaClient } from \"@prisma/client\";\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\nconst pool = createLakebasePool();\nconst adapter = new PrismaPg(pool);\nconst prisma = new PrismaClient({ adapter });\n\nconst users = await prisma.user.findMany();\n```\n\n### TypeORM\n\n```typescript\nimport { DataSource } from \"typeorm\";\nimport { createLakebasePool } from \"@databricks/lakebase\";\n\nconst pool = createLakebasePool();\n\nconst dataSource = new DataSource({\n  type: \"postgres\",\n  synchronize: true,\n  ...getLakebaseOrmConfig(),\n  entities: [\n    // Your entity classes\n  ],\n});\n\nawait dataSource.initialize();\n```\n\n### Sequelize\n\n```typescript\nimport { Sequelize } from \"sequelize\";\nimport { getLakebaseOrmConfig } from \"@databricks/lakebase\";\n\nconst sequelize = new Sequelize({\n  dialect: \"postgres\",\n  ...getLakebaseOrmConfig(),\n});\n```\n\n## OpenTelemetry Integration\n\nThe driver automatically uses OpenTelemetry's global registry when available. If your application initializes OpenTelemetry providers, the driver will automatically instrument queries and metrics with no additional configuration needed.\n\n### Setup\n\nInstall OpenTelemetry in your application:\n\n```bash\nnpm install @opentelemetry/api @opentelemetry/sdk-node\n```\n\nInitialize OpenTelemetry in your application:\n\n```typescript\nimport { NodeSDK } from \"@opentelemetry/sdk-node\";\n\nconst sdk = new NodeSDK({\n  // Your OTEL configuration\n});\n\nsdk.start(); // Registers global providers\n\n// Now create your pool - it automatically uses the global providers\nimport { createLakebasePool } from \"@databricks/lakebase\";\nconst pool = createLakebasePool();\n```\n\nThe driver calls `trace.getTracer('@databricks/lakebase')` and `metrics.getMeter('@databricks/lakebase')` internally. If no global providers are registered, operations are automatic no-ops.\n\n### Metrics Exported\n\n- `lakebase.token.refresh.duration` - OAuth token refresh duration (histogram, ms)\n- `lakebase.query.duration` - Query execution duration (histogram, ms)\n- `lakebase.pool.connections.total` - Total connections in pool (gauge)\n- `lakebase.pool.connections.idle` - Idle connections (gauge)\n- `lakebase.pool.connections.waiting` - Clients waiting for connection (gauge)\n- `lakebase.pool.errors` - Pool errors by error code (counter)\n\n## AppKit Integration\n\nThis driver is also available as part of [@databricks/appkit](https://www.npmjs.com/package/@databricks/appkit):\n\n```typescript\nimport { createLakebasePool } from \"@databricks/appkit\";\n\nconst pool = createLakebasePool();\n```\n\n**Differences between standalone and AppKit:**\n\n- **Standalone** (`@databricks/lakebase`): Silent by default - no logger configured\n- **AppKit** (`@databricks/appkit`): Automatically injects AppKit's logger with scope `appkit:connectors:lakebase`.\n\n## Learn more about Lakebase Autoscaling\n\nFor Lakebase Autoscaling documentation, see [docs.databricks.com/aws/en/oltp/projects](https://docs.databricks.com/aws/en/oltp/projects/).\n","readmeFilename":"README.md"}