How do Databricks Apps fit alongside BI tools and notebooks in a data platform?

Summary

• Databricks Apps add an interactive, read-write layer to a data platform. Where dashboards and notebooks help you view and explore governed data, apps let people act on it through custom interfaces and workflows.
• The three surfaces share one governed foundation. Apps, AI/BI Dashboards, and notebooks all query Unity Catalog tables directly, under the same row- and column-level security, and run on the same compute such as SQL warehouses.
• Pick the surface by the job: a dashboard for standard reporting, a notebook for exploration and development, and an app when you need input forms, writeback, business logic, or a custom UI a dashboard can't provide.
• Apps run on serverless compute and use workspace single sign-on, so there's no separate infrastructure to manage and no second login.
• Because everything sits on one platform, an app can reuse a data model built for a dashboard or drive an AI agent without copying data out.

How do Databricks Apps fit alongside BI tools and notebooks in a data platform?

Databricks Apps are the interactive, read-write surface of the platform. Dashboards and notebooks are mostly observational: a dashboard visualizes governed data for reporting, and a notebook is where you explore and develop. An app is operational, letting a user enter data, trigger logic, and run a workflow through a purpose-built interface. All three read the same governed tables through Unity Catalog, so they complement each other rather than duplicating the data.

What each surface is for

• AI/BI Dashboards: standard reporting and KPI tracking, presented as charts and tables over governed data. Read-focused.
• AI/BI Genie: ad-hoc questions asked in natural language against the same governed tables. Read-focused and conversational.
• Notebooks: exploratory analysis, data science, and development in code. Interactive and flexible.
• Databricks Apps: interactive applications with input, writeback, and custom logic, for when you need more than a view of the data.

Surface	Best for	Interaction
AI/BI Dashboards	Standard reporting, KPI tracking	Read, visual
AI/BI Genie	Ad-hoc natural-language questions	Read, conversational
Notebooks	Exploration, data science, development	Code, interactive
Databricks Apps	Input forms, writeback, workflows, custom UIs	Read-write, operational

One governed foundation

The surfaces share the parts that matter for trust and cost.

• Same data, same rules. Apps, dashboards, and notebooks query Unity Catalog tables directly, with no data movement, and Unity Catalog's row- and column-level security applies uniformly across all of them.
• Same compute. Apps run on Databricks serverless compute and use SQL warehouses to run queries, the same warehouses that power dashboards. Access is governed through the app's identity, so there is no connection string to hand-manage.
• Reuse across surfaces. An app can build on a data model defined for a dashboard, and business users can move between a dashboard, a Genie conversation, and a custom app without leaving the governed platform.

How Databricks approaches it

Databricks Apps deploy natively on the platform's serverless compute with automatic provisioning, so there is no separate application server to stand up. You build them in common Python frameworks (Streamlit, Dash, Flask, FastAPI) or JavaScript frameworks such as React, and authentication uses workspace single sign-on, so users don't log in twice. Finished apps can be published to and installed from Databricks Marketplace, with the data staying governed in the customer's own environment. For the full picture, see the introducing Databricks Apps blog and the Databricks Apps docs.

When to choose an app

• Strong fits: custom visualizations or layouts a standard dashboard widget can't produce; data entry, labeling, file upload, or writeback; business logic and workflows, like reviewing flagged transactions and taking an action; and front ends for AI agents that call tools and models.
• Weaker fits: a simple report (use AI/BI Dashboards); public or anonymous access, since apps require a Databricks identity; mobile or desktop distribution, since apps run in the browser; and hosting static content.

FAQs

Do Databricks Apps replace dashboards and notebooks?

No. They add an interactive, read-write layer. Dashboards stay best for reporting, notebooks for exploration and development, and apps for input, workflows, and custom interfaces, all on the same governed data.

Do apps, dashboards, and notebooks share the same data and security?

Yes. All query Unity Catalog tables directly, and Unity Catalog's row- and column-level controls apply the same way regardless of the surface you use.

What do I build a Databricks App with?

Common Python frameworks like Streamlit, Dash, Flask, and FastAPI, or JavaScript frameworks such as React. Apps run on serverless compute and use workspace single sign-on.

When should I pick an app over a dashboard?

Choose an app when you need data entry or writeback, custom logic or workflows, a bespoke interface, or a front end for an AI agent. For standard reporting, a dashboard is the simpler choice.