Big Data Analytics Just Got Easier with In-Database Capabilities for Databricks

[RamanK]

The Databricks cloud implementation of Apache Spark simplifies the use of the open-source big data processing engine, and cuts the time spent developing, scheduling, and managing complex Spark workloads. Databricks is focused on making big data simple, and with the Alteryx 10.6 release, blending big data with Databricks just got easier.  Alteryx users can now leverage the processing power of Spark to further expedite the speed at which large datasets are blended with in-database blending for Databricks.  

 

Through our partnership, Alteryx and Databricks expand the value of big data for a wider audience, making the power of Spark simple for business analysts.  The partnership empowers line-of-business analysts to ask questions of the largest datasets, uncover the fastest path to insights for massive data, and unlock the analytic compute power of Databricks.

In addition to in-database blending, data analysts and scientists alike can easily read and write to their Databricks cloud with Alteryx.  The Alteryx Connect In-DB tool enables users to easily to pull and read Databricks data in Alteryx workflows. Write support is available via the Databricks Bulk Loader, also configurable in the Connect In-DB tool.

Ready to try the latest and greatest Databricks and big data Alteryx tools? Please visit our Databricks help page for details on how to get started.