Deployment Models

When building a data or AI product on Databricks, one of the first architectural decisions is selecting the right deployment model. This choice determines where infrastructure lives, who manages it, and how your customers interact with the platform.

Overview

Model	Description
Partner Hosted (SaaS)	You own and operate the entire Databricks environment. Customers access your product as a service.
Customer Managed	Customer owns everything. You provide software, guidance, or templates.

Comparison

Factor	Partner Hosted	Customer Managed
Infrastructure ownership	Partner	Customer
Data location	Partner's environment	Customer's environment
Operational responsibility	Partner	Customer
Customer Databricks account required	No	Yes
Data residency control	Low	High
Partner control over platform	High	None
Implementation complexity	Lower	Higher
Customer onboarding effort	Minimal	Significant

Choosing a Model

When selecting a deployment model, consider:

1. Data residency requirements — Does your customer's data need to stay in their environment?

2. Operational capacity — Do you want to manage infrastructure, or does the customer prefer to?

3. Customer sophistication — Does the customer have a platform team capable of managing Databricks?

4. Regulatory constraints — Are there compliance requirements dictating where data can reside?

5. Scale and economics — Which model provides the best unit economics for your business?

Partners may offer two deployment models to serve different customer segments—Partner Hosted for customers seeking simplicity, and Customer Managed for enterprise customers with specific data residency or compliance requirements.

Application Architecture

For most Built On Databricks products, you will build an application that sits between your end users and the Databricks platform. A typical application architecture follows a layered system where each layer has clear responsibilities and security boundaries. This architecture ensures that Databricks credentials never reach the client, establishes clear authentication boundaries, and allows the system to scale independently at each layer.

The Five Layers:

1. Client Layer — Browser-based frontend (React, Angular, Vue) that renders UI and makes authenticated API requests
2. Authentication Layer — OAuth 2.0/OIDC integration with your identity provider for user authentication and session management
3. Backend Layer — Server-side API routes that validate sessions, manage authentication tokens, and proxy all Databricks API calls
4. Data Layer — Application database (PostgreSQL, MySQL) storing users, organizations, and encrypted credentials
5. Databricks Platform — Unity Catalog, SQL Warehouses, DBFS, Jobs, and other Databricks services accessed via REST APIs

For a detailed breakdown of each layer's responsibilities, security considerations, and technology recommendations, see the Firefly Analytics architecture documentation.

What's Next

• Partner Hosted (SaaS) — Full control, customers consume as a service
• Customer Managed — Customer-owned infrastructure