Databricks isn’t a cloud service but can be deployed on various cloud platforms like Google Cloud Platform (GCP) and Microsoft Azure. Here’s a breakdown of both options:

• Databricks on Google Cloud (GCP): This leverages Google’s Kubernetes Engine (GKE) to run containerized Databricks deployments. This translates to:
  • Faster execution of workloads at lower costs.
  • Easier migration of existing Databricks workloads to GCP.
  • Integration with other GCP solutions like BigQuery, Pub/Sub, Looker, and AI Platform.
• Azure Databricks: This is a fully managed service offered directly by Microsoft within the Azure cloud environment. Here are some key features:
  • Quick and easy setup through the Azure portal.
  • Tight integration with other Azure services.
  • Scalable environment for data warehousing, analytics, and AI workloads.
  • Open data lakehouse architecture for managing structured and unstructured data.

Choosing between them depends on your existing cloud infrastructure and specific needs. Databricks on GCP might offer a smoother integration if you’re already on GCP. On the other hand, if you prefer a fully managed service within the Azure ecosystem, Azure Databricks could be a better fit.