Sigma on Databricks: Cloud-native Analytics Built for Modern Business
Empower your data and business teams to explore, analyze, & decide from live data on the Databricks Lakehouse

Connect to your Data Lakehouse in seconds and start exploring, analyzing, and reporting on massive live datasets with Sigma

Sigma + Databricks
Sigma is the only cloud analytics and business intelligence solution for Databricks that empowers business teams to break free from the confines of the dashboard and SQL, explore live data independently, and make better, faster decisions. Together, Sigma and Databricks bring your data to life for your entire organization.
Why Sigma + Databricks?Reduce Time to Insight
Actively explore your data and conduct
complex "what if" ad hoc analyses. Sigma lets your data and business teams explore live data from Databricks using a familiar spreadsheet interface.
Live Connection to Databricks
Connect to Databricks Lakehouse in seconds using your cloud compute via Classic and Pro or with their cloud compute via Serverless
Work across multiple data sources safely and securely
With Sigma, your data never leaves Databricks. No extracts, ETL processes, or data migration needed. Everything stays where it belongs and all operations are executed inside the Lake house.
With access to Sigma on Databricks’ Lakehouse, data teams can easily make the results of their work digestible for business users, as well as make ad hoc analytics easy and accessible for every user.
VP of ISV Partners
Hear from our joint customers
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Chief Technology Officer
“In the last few years, Greenland has been thoughtful in its approach to its data stack. We needed a platform to bridge the gap between our data warehouse, our data catalog, and, ultimately, the analysis we do on a day-to-day basis. Partnering with Databricks and Sigma allowed us to organize, explore and analyze our data in order to work efficiently and deliver data outputs for general consumption.”
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Senior Data Scientist
“Using Sigma we were able to conduct exploratory ad hoc analysis on 50M rows of data across five departments easily and efficiently. This helped us reduce our time-to-insight and as an institutional brokerage, time is money.”