What is the difference between Azure Databricks and Databricks from the company called Databricks?

The differences between Azure Databricks and Databricks from the company called Databricks can be categorized into ownership, management, and integration:

Ownership:

  • Azure Databricks: Is a managed service offered by Microsoft within the Azure cloud platform. Microsoft manages the underlying infrastructure and Databricks provides the software and platform services.
  • Databricks: Is a standalone platform offered directly by the Databricks company. You either run it on your own infrastructure or on a cloud provider like AWS or GCP (Google Cloud Platform).

Management:

  • Azure Databricks: Users interact with the platform through the Azure portal and utilize Azure-specific features and services for resource management, security, and monitoring.
  • Databricks: Users manage the platform directly through the Databricks user interface and control all aspects of infrastructure, security, and configuration.

Integration:

  • Azure Databricks: Seamlessly integrates with other Azure services, making it ideal for existing Azure users and leveraging Azure-specific features like Azure Active Directory for access control and Azure Data Lake Storage for data storage.
  • Databricks: Offers broader cloud flexibility, allowing deployment on various cloud platforms and integrating with their native services. It provides its own security and access control features.

In summary:

Choose Azure Databricks if:

  • You prefer a managed service within the Azure ecosystem and seamless integration with Azure services.
  • You already use Azure for other workloads and benefit from centralized management and billing.

Choose Databricks if:

  • You require broader cloud flexibility and want to avoid being locked into a specific cloud provider.
  • You value greater control over your platform infrastructure and configuration.

Ultimately, the best choice depends on your specific needs, cloud preference, and existing infrastructure. Both options offer the same core Databricks functionalities and capabilities for data processing and analytics.