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Data Engineering
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Connecting Applications and BI Tools to Databricks SQL

isaac_gritz
Databricks Employee
Databricks Employee

Access Data in Databricks Using an Application or your Favorite BI Tool

You can leverage Partner Connect for easy, low-configuration connections to some of the most popular BI tools through our optimized connectors. Alternatively, you can follow these setup guides to connect to an even broader range of BI tools (AWS, Azure, GCP) via optimized connectors or JDBC/ODBC.

To submit SQL queries against data in Delta Lake using Databricks SQL warehouses via an application, you can leverage a JDBC/ODBC (AWS, Azure, GCP) connection or via our open-source Go, Node.js, Python and CLI connectors.

Let us know what you think in the comments! Have you been able to successfully connect an application or BI tool to the Lakehouse?

1 REPLY 1

ManeeshJha
New Contributor II

Great summary, Isaac. One thing I'd add from implementation experience is choosing the connector based on the consumption pattern, not just the BI tool.Partner Connect is perfect for quick PoCs and for analysts who just need Power BI / Tableau to work. But for production workloads, we have seen issues with PAT token expiry and lack of centralized governance.For app-layer access to Databricks SQL warehouses, what has worked better for us:For BI at scale: Use ODBC/JDBC with OAuth M2M instead of PAT. Easier to rotate and audit. If you're on AWS/Azure, use instance profile / managed identity based auth.For custom apps: The new Go / Node.js / Python SQL connectors are much lighter than JDBC. We recently replaced a JDBC wrapper with the Python connector for a low-latency API and saw โˆผ40% reduction in connection time.Performance tip: Don't forget HTTP Path vs JDBC URL confusion. Many failures we debug are due to using cluster path instead of SQL warehouse path.At Wronit, where we work on data engineering and lakehouse implementations, we generally recommend Partner Connect for business users and native SQL connectors + secrets management for application integrations.Curious to know if anyone has tested the new Statement Execution API vs direct SQL warehouse connection for high concurrency use cases?