How to Connect Databricks with Web and Mobile Apps

[tarunnagar]

Hi everyone,

I’m exploring ways to leverage Databricks for building data-driven web and mobile applications and wanted to get some insights from this community. Databricks is great for processing large datasets, running analytics, and building machine learning models, but I’m curious about the best practices for connecting it with apps in a seamless way.

Some areas I’m particularly interested in:

• APIs and Integration Methods – What are the most effective ways to expose Databricks data to apps? REST APIs, JDBC/ODBC connectors, or custom microservices?
• Real-Time vs Batch Data – For apps that require live updates (like dashboards or notifications), what’s the best approach to feed Databricks data in real-time without performance issues?
• Authentication & Security – What’s the recommended way to secure data when it’s accessed by web or mobile clients?
• Scalability Considerations – Any tips for handling high traffic apps that rely heavily on Databricks for analytics or recommendations?
• Best Practices & Tools – Are there frameworks, SDKs, or libraries that make integration easier for both web and mobile platforms?

I’d love to hear from anyone who has successfully connected Databricks to an app — any tips, examples, or pitfalls to avoid would be super helpful.

Looking forward to your insights!

[jameswood32]

To connect Databricks with web or mobile apps, most developers recommend exposing your data or models through a lightweight API layer. Use Databricks SQL Endpoints or MLflow model serving to generate secure REST endpoints your app can call directly. For more control, build a small API gateway using FastAPI, Flask, or Node.js and let it query Databricks via the Databricks REST API or JDBC/ODBC. Make sure to use service principals and token-based auth for security. Cache frequent queries with Redis or Cloudflare to reduce latency. This setup keeps your app fast while letting Databricks handle all heavy processing.