What differentiates a star schema from a snowflake schema?

A star schema is characterized by its structure, where a central fact table is directly linked to one or more dimension tables. This design facilitates fast retrieval of data, as the dimension tables are denormalized, meaning they contain all attributes related to a particular dimension in one single table. This simplicity in design leads to straightforward queries, making star schemas popular in data warehousing environments.

In contrast, a snowflake schema takes a more complex approach by normalizing dimension tables into multiple related tables. This means that dimension tables are broken down into sub-tables, which can lead to more efficient storage and reduced data redundancy but can complicate queries because multiple joins may be necessary to retrieve data.

Given this understanding, the distinction lies clearly in the structural organization of the data; star schemas prioritize fast query performance through a simpler table structure, while snowflake schemas emphasize normalization, resulting in a more complex but potentially more organized data model.