Delta Caching is an edge feature available in Databricks. This means it's not available in OSS Spark. Spark caching is also available in Databricks.

At a high level, Delta caching is storing the data in the data disk of the executors for repeated access. Spark caching is storing the data in memory or disk or both for repeated access. The caching mechanism is different in the way eviction and refresh are done.

A comparison is provided here :

https://docs.databricks.com/delta/optimizations/delta-cache.html#delta-and-apache-spark-caching