# FAQ

## Integrations[​](#integrations "Direct link to Integrations")

### What Databricks services are available through AppKit?[​](#what-databricks-services-are-available-through-appkit "Direct link to What Databricks services are available through AppKit?")

AppKit provides built-in integrations with the following Databricks services via its [plugin system](./docs/plugins.md):

| Plugin                                                 | Databricks Service                | What It Does                                                                            |
| ------------------------------------------------------ | --------------------------------- | --------------------------------------------------------------------------------------- |
| [Analytics](./docs/plugins/analytics.md)         | SQL Warehouses                    | Execute parameterized SQL queries with built-in caching, retry, and Arrow support       |
| [Lakebase](./docs/plugins/lakebase.md)           | Lakebase Autoscaling (PostgreSQL) | Relational database access via standard pg.Pool with automatic OAuth token refresh      |
| [Genie](./docs/plugins/genie.md)                 | AI/BI Genie Spaces                | Natural language data queries with conversation management and streaming                |
| [Files](./docs/plugins/files.md)                 | Unity Catalog Volumes             | Multi-volume file operations (list, read, upload, download, delete, preview)            |
| [Model Serving](./docs/plugins/model-serving.md) | Model Serving                     | Authenticated proxy to Model Serving endpoints with invoke and streaming support        |
| [Server](./docs/plugins/server.md)               | N/A                               | Express HTTP server with static file serving, Vite dev mode, and plugin route injection |

Stay tuned for new plugins as we constantly expand integrations!

### Can I add custom integrations?[​](#can-i-add-custom-integrations "Direct link to Can I add custom integrations?")

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](./docs/plugins/custom-plugins.md).

## Authentication[​](#authentication "Direct link to Authentication")

### How does authentication work in AppKit apps?[​](#how-does-authentication-work-in-appkit-apps "Direct link to How does authentication work in AppKit apps?")

AppKit apps are designed to run on [Databricks Apps](https://docs.databricks.com/aws/en/dev-tools/databricks-apps/), which handles user authentication and authorization. Databricks Apps forwards user identity to the app via request headers, and AppKit integrates with this through the `.asUser(req)` pattern for on-behalf-of (OBO) execution — allowing plugins to act on behalf of the authenticated user.

For details on how authentication and authorization work in Databricks Apps, see the [official auth documentation](https://docs.databricks.com/aws/en/dev-tools/databricks-apps/auth).

## Databases[​](#databases "Direct link to Databases")

*Also: Lakebase, PostgreSQL, OLTP*

### How does AppKit handle databases?[​](#how-does-appkit-handle-databases "Direct link to How does AppKit handle databases?")

AppKit is a TypeScript SDK (Express + React) and does not manage databases directly.

To add database support, use the [Lakebase plugin](./docs/plugins/lakebase.md), which integrates with Lakebase Autoscaling.

AppKit also uses Lakebase for caching when it is available (see the [caching](#does-appkit-support-caching) section below).

You can manage Lakebase Autoscaling projects and branches using the dedicated agent skill from [Databricks Agent Skills](./docs/development/ai-assisted-development.md), installed with the Databricks CLI.

### How does database setup and permission management work in AppKit?[​](#how-does-database-setup-and-permission-management-work-in-appkit "Direct link to How does database setup and permission management work in AppKit?")

AppKit apps can have an attached Lakebase Autoscaling instance. No database is bundled by default - you add one by configuring the [Lakebase plugin](./docs/plugins/lakebase.md). When running `databricks apps init` and selecting the Lakebase plugin, the selected database is automatically attached as an app resource after deployment.

With [AI-assisted development](./docs/development/ai-assisted-development.md), you can also ask the Agent to create a Lakebase project and branch for you.

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.

### Does AppKit support Lakebase Provisioned?[​](#does-appkit-support-lakebase-provisioned "Direct link to Does AppKit support Lakebase Provisioned?")

No. AppKit only supports Lakebase Autoscaling. Lakebase Provisioned databases are not supported by the [Lakebase plugin](./docs/plugins/lakebase.md) or Lakebase agent skill from [Databricks Agent Skills](./docs/development/ai-assisted-development.md).

## Caching[​](#caching "Direct link to Caching")

### Does AppKit support caching?[​](#does-appkit-support-caching "Direct link to Does AppKit support caching?")

Yes. The [Analytics plugin](./docs/plugins/analytics.md) - used for executing SQL queries against Databricks SQL Warehouses - supports an optional cache layer.

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.

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.