True or False: Databricks Workflows supports workloads across multiple cloud service providers and tools.

Databricks Workflows indeed supports workloads across multiple cloud service providers and tools, making it a versatile option for organizations that may utilize a multi-cloud strategy. This capability allows users to orchestrate and manage end-to-end workflows that can integrate various services and tools across different environments, enhancing the flexibility and scalability of data processing and analysis tasks.

In a multi-cloud setup, organizations can leverage the strengths of different providers, unlocking additional functionalities and cost efficiencies. The support for multiple tools and services also facilitates seamless data movement and processing, which is essential for complex data workloads that require collaboration across platforms.

The other alternatives suggest limitations that do not align with the capabilities of Databricks Workflows. For instance, stating that it “depends on the configuration” might imply there's a restriction when in fact Databricks embraces the ability to cater to various configurations effortlessly. Similarly, claiming that it only works with specific providers doesn't encompass the breadth of integration options available within Databricks.

Overall, the architecture and design of Databricks Workflows promote extensive interoperability, enabling users to effectively manage and streamline their complex workflows across diverse cloud environments.