Spark Cluster or SQL Warehouse

When you create a data transformation job using Databricks Unity Catalog, you can either use a spark cluster or SQL warehouse as the compute resource to query data on Databricks. Here are some pointers to help you decide which option to choose, based on your specific use case.

• SQL Warehouse is designed to execute SQL commands, while Spark Clusters are designed to execute various types of commands like Scala, R, Python, and SQL.

• With SQL Warehouse , there is no need to manage libraries such as JAR, PIP, or WHL. Clusters on the other hand, can become overloaded with libraries, which in turn can impact the overall performance.

• SQL Warehouse can scale up and down like a cluster, however for a Spark Cluster it can scale up to the maximum range of configured nodes.

• SQL Warehouse simplifies SQL endpoint management accelerating the launch time. Configuration of Spark Clusters can be complex , especially for beginners.

• SQL Warehouse offers serverless capabilities, reducing the start time and also being cost-effective, while this is not the case with Spark Clusters.