Databricks Apps

Databricks Apps enables developers to build and deploy secure data and AI applications directly on the Databricks platform, which eliminates the need for separate infrastructure. Apps are hosted on the Databricks serverless platform and integrate with key platform services, including the following:

• Unity Catalog for data governance
• Databricks SQL for querying data
• Model Serving for deploying AI models
• Lakeflow Jobs for ETL and automation
• OAuth and service principals for authentication and authorization

You can develop your apps locally, deploy them to a workspace, and move them between workspaces. This hosting model eliminates the need for developers to handle security, infrastructure, and compliance, which simplifies the process of bringing internal data tools to production.

Databricks Apps supports Python frameworks like Streamlit, Dash, and Gradio. For examples that use popular Python frameworks in the Databricks Apps UI, see Develop Databricks apps.

For information about Databricks Apps pricing, see Compute for Apps.

Common use cases

Databricks apps work well for internal tools that combine data, AI, and automation. Example use cases include:

• Interactive data visualizations and embedded Business Intelligence (BI) dashboards
• Retrieval-Augmented Generation (RAG) chat apps powered by Genie
• Custom configuration interfaces for Lakeflow
• Data entry forms backed by Databricks SQL
• Business process automation combining multiple Databricks services
• Custom ops tools for alert triage and response

Limitations

• App files can't exceed 10 MB. If any file in the app directory exceeds this limit, deployment fails with an error.
• Databricks deletes app logs when the compute resource running the app is terminated. See View logs for your Databricks app.
• If you grant consent to an app through user authorization, you can't revoke that consent later.

Databricks Apps system environment

note

To view the environment for a specific app, including environment variables and installed packages, go to the Environment tab on the details page for the app. See View the details for a Databricks app.

The following describes the system environment in which your apps run. For a list of Python packages that are pre-installed with your app, see Define environment variables in a Databricks app.

• Operating System: Ubuntu 22.04 LTS
• Python environment: Python 3.11.0, running in a dedicated virtual environment. All dependencies are isolated within this environment, including libraries you install using a requirements.txt file and pre-installed libraries.
• System resources: Each app can use up to 2 virtual CPUs (vCPUs) and 6 GB of memory. If your app exceeds these limits, Databricks might restart it.

Compliance standard support

The following table lists the compliance standards supported by Databricks Apps and the corresponding regions where each standard applies. For guidance on how to meet these standards, see Compliance.

Compliance standard	Supported regions
PCI-DSS	All regions
HIPAA	All regions
FedRAMP Moderate	us-east-1, us-east-2, us-west-1, us-west-2
IRAP	ap-southeast-2
UKCE+	eu-west-2
K-FSI	ap-northeast-2
CCCS Medium	ca-central-1