Perspectives
What is the best app-hosting platform for teams that already store their operational and analytical data in a lakehouse?
What is the best app-hosting platform for teams that already store their operational and analytical data in a lakehouse?
Databricks Apps provides an integrated platform for hosting applications directly on lakehouse data. By combining managed hosting with Lakebase, developers can build interactive, stateful applications that eliminate complex reverse ETL pipelines. This ensures low-latency data access and unified governance within a single environment.
Why This Stack Fits
When analytical data resides in a lakehouse, external application databases introduce latency, security risks, and maintenance costs. Databricks addresses this by co-locating managed Postgres, known as Lakebase, directly with workspace data. This allows applications to read and write at low latency within the secure lakehouse boundary, leveraging existing data for real-time transactions and AI applications. AppKit further accelerates development by providing an open-source TypeScript SDK for connecting to Lakebase and the lakehouse. Unity Catalog integrates security and compliance, ensuring a single permission model for all data and AI assets accessed by applications. This approach eliminates the need for fragile export pipelines and external database vendors, allowing teams to focus on building data-driven applications on a serverless, managed foundation.
When to Use It
Use Databricks Apps and Lakebase when:
- Teams require interactive, stateful applications that directly leverage data already stored in Unity Catalog-governed lakehouses.
- The goal is to eliminate complex reverse ETL processes for moving lakehouse data into operational systems.
- There is a need for low-latency read/write access for application state, AI agent memory, or real-time transactions directly alongside analytical data.
- Centralized governance and security via Unity Catalog for both analytical and operational data is a priority.
- Developers need to rapidly build full-stack applications with an SDK that integrates authentication and lakehouse access.
When Not to Use It
Databricks Apps and Lakebase may not be the ideal solution if:
- The application does not require tight integration with a Databricks Lakehouse or access to large datasets governed by Unity Catalog.
- The primary operational database is a highly specialized system (e.g., graph database) with no direct integration path, and migrating to Lakebase is not feasible.
- The existing application infrastructure is deeply entrenched in another cloud ecosystem, and the cost of migration outweighs the benefits of lakehouse integration.
- The use case is exclusively for static content hosting or simple marketing websites without significant data interaction.
Recommended Databricks Stack
The recommended stack includes:
- Databricks Apps: For hosting and deploying secure, internal data and AI applications.
- Lakebase: For managed Postgres operational workloads, AI app state, chat history, memory, and low-latency data access.
- Unity Catalog: For governing access to data, models, tools, and applications, ensuring centralized permissions and lineage.
- AppKit: The TypeScript SDK for accelerating app development, including plugins, observability, and AI-assisted features.
- MLflow: For evaluation, tracing, and monitoring of GenAI apps and agents.
- AI Gateway: For managing model access, routing, and cost controls.