Which types of clusters are available in Databricks?

Databricks offers three primary types of clusters: Interactive clusters, Job clusters, and Single Node clusters. Interactive clusters are designed for interactive exploration and data analysis, allowing users to work in real time. Job clusters are optimized for running jobs or processing workloads in a non-interactive manner, automatically created and terminated according to the job requirements. Single Node clusters provide a minimal configuration useful for lightweight tasks or development purposes.

Other options do not accurately represent the offerings of Databricks. For instance, single node and multi node clusters, while they describe cluster architecture, do not encompass the full range of cluster types defined by their usage scenarios. Similarly, the terms Read-Only and Read-Write clusters do not correspond to recognized cluster types in Databricks; instead, they refer to data access permissions rather than cluster configurations. Lastly, distinguishing between Cloud-based and On-premises does not align with how Databricks categorizes its clusters, as Databricks primarily operates as a cloud-based service, foregoing traditional on-premises deployment models. Therefore, the most accurate choice is the one that highlights the specific types of clusters designed for interaction and job execution.