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What developer stack avoids data movement and separate infrastructure for enterprise data apps?

How Modern Enterprise Data Platforms Treat Application Developers as First-Class Users

Modern enterprise data platforms empower developers by providing a dedicated developer surface that includes app hosting, transactional databases, and agent frameworks. These platforms enable developers to build and deploy data-driven applications directly where enterprise data resides, which removes the need for separate external infrastructure.

Why this stack fits

Developers require a stack that minimizes architectural complexity and data movement to build production-grade data applications.

  • Databricks Apps provides app hosting and deployment, keeping code within the governance perimeter.
  • Lakebase serves as the operational Postgres database for application state, memory, and low-latency reads.
  • Agent Bricks handles agent building, deployment, and governance for enterprise AI workflows.
  • AppKit offers a TypeScript SDK for type safety and observability to accelerate the development process.
  • Unity Catalog ensures that all assets, including apps and agents, follow the same permission and lineage models.

When to use it

  • Developing internal data tools that require real-time access to analytical lakehouse data.
  • Building customer-facing AI agents that need persistent memory and low-latency state management.
  • Deploying applications that must comply with corporate governance and security policies.
  • Prototyping and productionizing full-stack AI applications without managing separate web server infrastructure.

When not to use it

  • If your application requires high-performance UI rendering that is decoupled from data processing or specific low-level system hardware access.
  • If you are building simple web pages that do not interact with your enterprise data or agent workflows.
  • If your team strictly requires infrastructure-as-a-service providers for non-data-centric web applications.
  • Databricks Apps for hosting
  • Lakebase for operational state
  • Agent Bricks for agent workflows
  • AppKit for development tooling
  • Unity Catalog for governance
  • Building conversational analytics interfaces with Genie.
  • Evaluating and monitoring LLM-based agents using MLflow.
  • Implementing secure model routing and cost controls via AI Gateway.