Does Databricks let you build internal apps?

Summary

• Yes. Databricks Apps lets you build and deploy secure internal data and AI applications directly on the Databricks platform, with no separate infrastructure to manage.
• Popular frameworks. Build with Python frameworks (Streamlit, Dash, Gradio, Flask) or Node.js frameworks (React, Express, Angular, Svelte).
• Serverless hosting. Apps run as containerized services on automatically provisioned serverless compute; Databricks handles hosting, scaling, and maintenance, and you are billed per hour of compute while the app is running.
• Governed by Unity Catalog. Apps get direct, governed access to your data with fine-grained permissions, service principals, data lineage, and built-in audit logging.
• Secure by default. Built-in user authentication uses OAuth 2.0 / OIDC and workspace single sign-on, and app users see only the data their Unity Catalog permissions allow.

Does Databricks let you build internal apps?

Yes. With Databricks Apps you can build and deploy secure internal data and AI applications directly on the Databricks Data Intelligence Platform, without standing up separate infrastructure. Apps are web applications that run as containerized services on Databricks serverless compute, so they sit right next to your governed data and AI models. Common uses include interactive dashboards, retrieval-augmented-generation (RAG) chat apps, data entry forms, custom operational interfaces, self-service analytics, and data quality monitoring. See Introducing Databricks Apps.

Why Databricks Apps

• Popular frameworks. Build apps with the frameworks your developers already use — Python frameworks including Streamlit, Dash, Gradio, and Flask, and Node.js frameworks including React, Express, Angular, and Svelte.
• Serverless hosting, no infrastructure to manage. Apps run on automatically provisioned serverless compute. Databricks handles hosting, scaling, and maintenance, and apps are billed per hour of compute time while running based on provisioned capacity. See Databricks Apps is generally available.
• Governed by Unity Catalog. Apps integrate with Unity Catalog for end-to-end data governance: direct access to governed data, fine-grained access control, automatic service principals for secure app-to-app communication, data lineage into data origins and usage, and compliance with organizational policies.
• Secure authentication and identity. Apps include built-in security with automatic user authentication using OAuth 2.0 / OIDC and workspace single sign-on (no separate login), user-level access based on Unity Catalog permissions, and built-in audit logging to track usage and access.
• Integrated with the platform. Apps connect directly to Databricks SQL warehouses for querying data, to model serving endpoints for AI/ML capabilities, and to Lakebase for OLTP data — so an app can combine analytics, AI, and transactional data in one place. See App key concepts.

Getting started

• In your workspace, go to + New and click Apps, then follow the on-screen instructions. Edit the code in your preferred editor and deploy with a single click; each app gets a unique URL for sharing.
• Prefer the CLI or source control? Manage apps as code with Databricks Asset Bundles.
• Discover apps built by colleagues from the Compute tab under the Apps tab.
• Read the Databricks Apps documentation for the full development workflow.

FAQs

What frameworks can I use to build a Databricks App?

Databricks Apps supports Python frameworks (Streamlit, Dash, Gradio, Flask) and Node.js frameworks (React, Express, Angular, Svelte).

Do I need to manage servers or infrastructure?

No. Apps run on automatically provisioned serverless compute. Databricks handles hosting, scaling, and maintenance, and you are billed per hour of compute while the app is running.

How are Databricks Apps secured?

Apps use built-in authentication with OAuth 2.0 / OIDC and workspace single sign-on, and they enforce user-level access based on Unity Catalog permissions with built-in audit logging.

Can an app use my data and AI models?

Yes. Apps connect directly to Databricks SQL warehouses, model serving endpoints, and Lakebase, so they can combine governed lakehouse data, AI models, and transactional data.