https://github.com/databricks/appkit
https://github.com/databricks/appkit
Last synced: 24 days ago
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- Host: GitHub
- URL: https://github.com/databricks/appkit
- Owner: databricks
- License: apache-2.0
- Created: 2025-12-05T09:39:45.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2026-03-10T16:51:09.000Z (26 days ago)
- Last Synced: 2026-03-10T17:55:36.272Z (26 days ago)
- Language: TypeScript
- Homepage:
- Size: 3.29 MB
- Stars: 14
- Watchers: 0
- Forks: 5
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
- Notice: NOTICE.md
- Dco: DCO
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README
# AppKit
Build Databricks Apps faster with our brand-new Node.js + React SDK. Built for humans and AI.
> [!WARNING]
> PREVIEW - NOT FOR PRODUCTION USE
> **This SDK is in preview and is subject to change without notice.**
>
> - ❌ **Do NOT use in production environments**
> - ⚠️ **Breaking changes may occur at any time**
> - 🔬 **APIs are experimental and unstable**
> - 📝 **Use for development and testing only**
>
## Introduction
AppKit is a TypeScript SDK for building production-ready Databricks applications with a plugin-based architecture. It provides opinionated defaults, built-in observability, and seamless integration with Databricks services.
AppKit simplifies building data applications on Databricks by providing:
- **Plugin architecture**: Modular design with built-in server and analytics plugins
- **Type safety**: End-to-end TypeScript with automatic query type generation
- **Production-ready features**: Built-in caching, telemetry, retry logic, and error handling
- **Developer experience**: Remote hot reload, file-based queries, optimized for AI-assisted development
- **Databricks native**: Seamless integration with SQL Warehouses, Unity Catalog, and other workspace resources
## Plugins
AppKit's power comes from its plugin system. Each plugin adds a focused capability to your app with minimal configuration.
### Available now
- **Analytics Plugin** — Query your Lakehouse data directly from your app. Define SQL queries as files, execute them against Databricks SQL Warehouses, and get automatic caching, parameterization, and on-behalf-of user execution out of the box. Perfect for building apps that surface insights from your Lakehouse.
### Coming soon
- **Genie Plugin** — Conversational AI interface powered by Databricks Genie
- **Files Plugin** — Browse, upload, and manage files in Unity Catalog Volumes
- **Lakebase Plugin** — OLTP database operations with automatic OAuth token management
- ...and this is just the beginning.
> Missing a plugin? [Open an issue](https://github.com/databricks/appkit/issues/new) and tell us what you need — community input directly shapes the roadmap.
## Getting started
Follow the [Getting Started](https://databricks.github.io/appkit/docs/) guide to get started with AppKit.
🤖 For AI/code assistants, see the [AI-assisted development](https://databricks.github.io/appkit/docs/development/ai-assisted-development) guide.
## Documentation
📖 For full AppKit documentation, visit the [AppKit Documentation](https://databricks.github.io/appkit/) website.
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup and contribution guidelines.