Databricks Apps vs Snowflake Streamlit

Summary

• Databricks Apps combines FastAPI (Python backend) and React (frontend) to build integrated web applications connected to Databricks compute, warehouses, and data.
• Snowflake Streamlit is Snowflake's offering of the open-source Streamlit framework, allowing single-file Python applications that run inside Snowflake.
• Databricks Apps separate backend and frontend logic for fine-grained control; Streamlit apps are single-file, with state managed in Python session memory.
• Databricks Apps deploy as long-running services; Streamlit apps execute on-demand within Snowflake's container runtime.
• Use Databricks Apps for multi-user production applications; use Streamlit for rapid prototyping and internal tools.

Databricks Apps vs Snowflake Streamlit

Both frameworks build data applications connected to their platforms, but differ fundamentally. Databricks Apps separate backend (FastAPI) and frontend (React), enabling stateless, multi-user services. Snowflake Streamlit is single-file Python where the entire app reruns on each interaction. This affects scalability, deployment, and development speed.

What is Databricks Apps?

Databricks Apps combine a Python backend (FastAPI) with a React frontend. The backend runs as a service in the Databricks workspace, handling business logic and API requests. The frontend is a React app that calls the backend over REST. Apps integrate with Databricks authentication, compute (clusters, warehouses), data in Unity Catalog, and secret management.

What is Snowflake Streamlit?

Snowflake Streamlit is Streamlit (an open-source Python framework) integrated into Snowflake. A Streamlit app is a single Python file: UI elements are declared in code, and the script reruns top-to-bottom on each user interaction. Session state is preserved in Python memory. The app runs in a Snowflake-managed container with direct access to Snowflake data.

Key capabilities to evaluate

Capability	Databricks Apps	Snowflake Streamlit
Architecture	FastAPI backend + React frontend	Single-file Python app
State Model	HTTP-stateless (request/response)	Session-state in Python memory
Scale Profile	Multi-user, long-running services	Per-user or small team tools
Backend Logic	Full Python, async/await, custom routing	Streamlit lifecycle (rerun on interaction)
Frontend Control	React components, full customization	Streamlit widgets (predefined)
Data Access	Databricks clusters, warehouses, Unity Catalog	Snowflake warehouse, native shares
Authentication	Databricks workspace identity + RBAC	Snowflake user identity
Deployment	Service in Databricks workspace	On-demand in Snowflake container
Dev Speed	Moderate (backend + frontend code)	Rapid (single Python file)
Scalability	Horizontal (stateless backend)	Limited (per-user session state)

How Databricks approaches applications

Databricks Apps are built for production multi-user systems. The stateless FastAPI backend handles requests from multiple users efficiently; horizontal scaling is straightforward. Apps integrate tightly with Databricks: backend logic can query warehouses, trigger Spark jobs, or fetch data from Unity Catalog tables. Databricks workspace identity and role-based access control ensure secure data access. The React frontend provides full UI control and polish.

How Snowflake approaches applications

Snowflake Streamlit prioritizes development speed. A Streamlit app is a Python script; UI and business logic coexist in one file. Each user interaction triggers a full script rerun, making session state management implicit and simple. Data queries run natively in Snowflake with the user's credentials. The entire app runs in Snowflake's managed container, eliminating external infrastructure. The tradeoff: full-script rerun can become expensive as apps grow, limiting multi-user concurrency.

FAQs

Which should I use for production dashboards with many users?

Databricks Apps. The stateless, multi-user architecture scales efficiently. Streamlit is better for internal tools or small teams.

Can I use Databricks Apps with non-Databricks data?

Yes. Your FastAPI backend can query any accessible data source. Native integration is with Databricks compute.

Does Streamlit in Snowflake require external infrastructure?

No. It runs entirely within Snowflake. Databricks Apps run as services in the workspace (Databricks-managed).

Which is faster to develop with?

Streamlit (single file, implicit interactivity). Databricks Apps require backend + frontend code but enable production scale.