Azure Databricks Now Available in Azure Government (Public Preview)
We are excited to announce that Azure Databricks is now in Microsoft’s Azure Government region, enabling new data and AI use cases for...
The data community raised a total of $101,626 to help organizations fight racial injustice. Thank you to all who donated!
Our commitment to diversity and inclusion is inherent in our company values at Databricks, but recent events and protests around the world have...
Allow Simple Cluster Creation with Full Admin Control Using Cluster Policies
What is a Databricks cluster policy? A Databricks cluster policy is a template that restricts the way users interact with cluster configuration. Today...
Databricks Announces 2020 North America Partner Awards
Databricks has a great partner ecosystem of over 450 partners that are critical to building and delivering the best data and AI solutions...
Meet the 2020 Databricks Data Team Awards Winners
On the closing day of Spark + AI Summit, Databricks CEO Ali Ghodsi recognized three exceptional data teams for how they came together...
Introducing the Next-Generation Data Science Workspace
At today’s Spark + AI Summit 2020, we unveiled the next generation of the Databricks Data Science Workspace: An open and unified experience...
MLflow Joins the Linux Foundation to Become the Open Standard for Machine Learning Platforms
Watch Spark + AI Summit Keynotes here At today's Spark + AI Summit 2020, we announced that MLflow is becoming a Linux Foundation...
Introducing GlowGR: An industrial-scale, ultra-fast and sensitive method for genetic association studies
Today, we announce that we are making a new whole genome regression method available to the open source bioinformatics community as part of...
Welcoming Redash to Databricks
This morning at Spark and AI Summit, we announced that Databricks has acquired Redash, the company behind the popular open source project of...
Introducing Koalas 1.0
Koalas was first introduced last year to provide data scientists using pandas with a way to scale their existing big data workloads by...