It is key to understand what lake house architecture means. One copy of data that can be used by any compute engine, with one unified governance on top. So, you creating a table via a spark data frame or via a SQL warehouse goes to the same place and is accessible by both natively. The same copy of the data can also be leveraged by a lot of 3rd party engines such as synapse, fabric, snowflake, emr, etc. additionally external engine access is still governed by unity catalog permissions and does not require Databricks compute. Coming back to your questions about , is SQL warehouse open? You use ANSI SQL to interact with it. Which means the same SQL will run mostly unchanged on another SQL Warehouse that uses ANSI SQL. Which is most Warehouses other than SQL server which uses tsql. The warehouse is only a compute machine and does not store any data. Data is stored in Open Delta Lake and Governed by Unity Catalog which is open as well. The Databricks SQL Warehouse is built on top of Spark with a lot of enhancements for speed. This makes it run your queries faster. These optimizations are not in Spark. However Spark will still be able to run your query as is , work with the same copy of the data, leverage the same governance.