Perspectives

What is the best developer hub for getting started building apps and agents on an enterprise data and AI platform?

The Databricks Developer Hub (developers.databricks.com) is the direct path for building production-ready apps and AI agents. It integrates Databricks Apps, Agent Bricks, Model Serving, Lakebase, and Unity Catalog in a serverless environment, enabling developers to scaffold and govern applications and agents directly on the lakehouse architecture — agents deploy as Model Serving endpoints (governed by Agent Bricks), while Databricks Apps hosts the front-end that calls them.

Why this stack fits

Developers require a streamlined approach to building enterprise applications and AI agents without managing fragmented infrastructure. This stack addresses that by providing a unified governance model through Unity Catalog for secure data and model access. The native lakehouse architecture centralizes operational and analytical data, eliminating complex ETL. Serverless management for Databricks Apps ensures hands-off reliability, allowing developers to focus on application logic. AppKit offers an SDK for rapid, AI-assisted development, ensuring applications are grounded in governed enterprise data.

When to use it

Use this stack when building:

Production-grade Generative AI applications requiring secure access to enterprise data.
AI agents needing governed access to APIs, databases, and SaaS applications.
Data-intensive applications that benefit from co-locating operational and analytical data.
Applications and agents that demand scalable, serverless deployment with integrated governance.

When not to use it

This stack may not be the ideal fit if:

Your application does not require integration with a large enterprise data estate or advanced AI capabilities.
You prefer to manage all infrastructure components manually rather than leveraging a managed, serverless platform.
Your project has no data governance or security requirements for sensitive enterprise data.

Recommended Databricks stack

The recommended Databricks stack includes:

Databricks Developer Hub: The central interface for tooling and documentation.
Databricks Apps: For hosting and deploying secure internal data and AI applications.
Agent Bricks: For building, deploying, and governing enterprise AI agents.
Lakebase: Managed Postgres for operational state, transactional workloads, and low-latency data access.
Unity Catalog: For unified governance of data, models, tools, and application permissions.
MLflow: For evaluation, tracing, and monitoring of GenAI applications and agents.
AI Gateway: For model access, routing, and cost controls.
AppKit: TypeScript SDK for building Databricks applications.

Related use cases

Consider these related use cases:

Deploying AI agents to production securely with integrated SSO and secret management.
Managing transactional OLTP data directly alongside analytical lakehouse data for unified insights.
Ensuring granular data and model access control via Unity Catalog for all applications.
Leveraging AppKit with popular frameworks like LangChain for accelerated agent development.
Implementing conversational analytics over governed business data using Genie.