With AtScale and Databricks together, the data can stay in the Databricks cluster with all queries running directly against that cluster, eliminating the need for data movement. This implementation style supports many tools, including the Microsoft stack, Tableau, Looker, and data science tools via a Python interface. Best of all, users are able to access hundreds of billions or even trillions of rows without the risk of running out of resources. AtScale helps Databricks customers remove the complexities of managing a separate optional serving layer, replacing it with direct, live access to AtScale with an effortless drag and drop interface.
Combining AtScale with Databricks Lakehouse helps companies eliminate the need for siloed data warehouses and costly data movements within the cloud, delivering unified, live queries that work with any BI platform. Replacing your legacy Cube architectures like SSAS will enable dimensional analysis in milliseconds. Check out our blog post How to Scale SSAS-Style Analytics with Databricks + AtScale to learn more.