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Application

Azure Databricks

Azure Databricks is a cloud "lakehouse" platform that can handle both data warehouse and data lake workloads. 

It allows users to create and run data pipelines, and develop and deploy analytics and machine learning models. Azure Databricks is based on Spark, providing automated cluster management and Python-style notebooks (Databricks data pipelines). 

Azure Databricks

Azure Databricks is a cloud "lakehouse" platform that can handle both data warehouse and data lake workloads. 

It allows users to create and run data pipelines, and develop and deploy analytics and machine learning models. Azure Databricks is based on Spark, providing automated cluster management and Python-style notebooks (Databricks data pipelines). 

Control-M for Azure Databricks enables you to do the following:

  • Connect to any Azure Databricks workspace using service principal authentication.
  • Integrate Azure Databricks jobs with other Control-M jobs into a single scheduling environment.
  • Trigger and monitor your Azure Databricks jobs and view the results in the Monitoring domain.
  • Attach an SLA job to your entire Azure Databricks data service.
  • Introduce all Control-M capabilities to Azure Databricks, including advanced scheduling criteria, complex dependencies, quantitative and control resources, and variables.
  • Run 50 Azure Databricks jobs simultaneously per Control-M/Agent.

Control-M for Azure Databricks is available for these product versions:

  • Control-M 20.200 and later
  • BMC Helix Control-M 21 and later

Supporting Documentation

For more information on this integration, including how to create a connection profile and define a job, please visit:

Integrating Azure Databricks and Control-M

BMC Helix Control-M for Azure Databricks

Topic

Business & IT Automation

Publisher

BMC Software