Snowflake schema architecture is a more complex variation of a star schema design. The main difference is that dimensional tables in a snowflake schema are normalized, so they have a typical relational database design.

Snowflake schemas are generally used when a dimensional table becomes very big and when a star schema can’t represent the complexity of a data structure. For example if a PRODUCT dimension table contains millions of rows, the use of snowflake schemas should significantly improve performance by moving out some data to other table (with BRANDS for instance).

The problem is that the more normalized the dimension table is, the more complicated SQL joins must be issued to query them. This is because in order for a query to be answered, many tables need to be joined and aggregates generated.

An example of a snowflake schema architecture is depicted below.