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| # FAQ | ||
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| ## Integrations | ||
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| ### What Databricks services are available through AppKit? | ||
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| AppKit provides built-in integrations with the following Databricks services via its [plugin system](./plugins/): | ||
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| | Plugin | Databricks Service | What It Does | | ||
| | --- | --- | --- | | ||
| | [Analytics](./plugins/analytics) | SQL Warehouses | Execute parameterized SQL queries with built-in caching, retry, and Arrow support | | ||
| | [Lakebase](./plugins/lakebase) | Lakebase Autoscaling (PostgreSQL) | Relational database access via standard pg.Pool with automatic OAuth token refresh | | ||
| | [Genie](./plugins/genie) | AI/BI Genie Spaces | Natural language data queries with conversation management and streaming | | ||
| | [Files](./plugins/files) | Unity Catalog Volumes | Multi-volume file operations (list, read, upload, download, delete, preview) | | ||
| | [Serving](./plugins/serving) | Model Serving | Authenticated proxy to Model Serving endpoints with invoke and streaming support | | ||
| | [Server](./plugins/server) | N/A | Express HTTP server with static file serving, Vite dev mode, and plugin route injection | | ||
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| Stay tuned for new plugins as we constantly expand integrations! | ||
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| ### Can I add custom integrations? | ||
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| Yes. AppKit's plugin architecture is extensible - you can create custom plugins using the CLI (`npx appkit plugin create`) or manually. See the [creating custom plugins guide](./plugins/custom-plugins). | ||
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| ## Databases | ||
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| *Also: Lakebase, PostgreSQL, OLTP* | ||
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| ### How does AppKit handle databases? | ||
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| AppKit is a Node.js + React SDK and does not manage databases directly. | ||
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| To add database support, use the [Lakebase plugin](./plugins/lakebase), which integrates with Lakebase Autoscaling. | ||
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| AppKit also uses Lakebase for caching when it is available (see the [caching](#does-appkit-support-caching) section below). | ||
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| You can manage Lakebase Autoscaling projects and branches using the dedicated agent skill from [Databricks Agent Skills](./development/ai-assisted-development), installed with the Databricks CLI. | ||
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| ### How does database setup and permission management work in AppKit? | ||
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| AppKit apps can have an attached Lakebase Autoscaling instance. No database is bundled by default - you add one by configuring the [Lakebase plugin](./plugins/lakebase). When running `databricks apps init` and selecting the Lakebase plugin, the selected database is automatically attached as an app resource after deployment. | ||
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| With [AI-assisted development](./development/ai-assisted-development), you can also ask the Agent to create a Lakebase project and branch for you. | ||
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| When deployed, a Databricks app uses its Service Principal for schema and table creation. If you configure the Lakebase Autoscaling project as an [app resource](https://docs.databricks.com/aws/en/dev-tools/databricks-apps/resources), the necessary connect and create permissions are granted automatically to the app's Service Principal. | ||
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| ### Does AppKit support Lakebase Provisioned? | ||
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| No. AppKit only supports Lakebase Autoscaling. Lakebase Provisioned databases are not supported by the [Lakebase plugin](./plugins/lakebase) or Lakebase agent skill from [Databricks Agent Skills](./development/ai-assisted-development). | ||
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| ## Caching | ||
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| ### Does AppKit support caching? | ||
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| Yes. The [Analytics plugin](./plugins/analytics) - used for executing SQL queries against Databricks SQL Warehouses - supports an optional cache layer. | ||
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| Caching is configured per plugin and can use either [Lakebase Autoscaling](https://docs.databricks.com/aws/en/oltp/) or an in-memory store, depending on the configuration. | ||
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| If the Lakebase Autoscaling connection is configured, the AppKit-based app creates an `appkit` schema in the configured database with internal tables required for caching. | ||
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