In the previous two articles, we considered the two most common data warehouse models: the star schema and the snowflake schema. Today, we’ll examine the differences between these two schemas and we’ll explain when it’s better to use one or the other.The star schema and the snowflake schema are ways to organize data marts or entire data warehouses using relational databases. Both of them usedimension tablesto describe data aggregated in a
In a previous article we discussed the star schema model. The snowflake schema is next to the star schema in terms of its importance in data warehouse modeling. It was developed out of the star schema, and it offers some advantages over its predecessor. But these advantages come at a cost. In this article, we’ll discuss when and how to use the snowflake schema.The Snowflake SchemaThe snowflake schema’s name comes from the fact that dimension tables branch out and look something like a snowflake. When we look at the model above, we’ll notice it’s a fact table surrounded by a few dimension tables, some of which do the aforementioned branching. Unlike the star schema, dimension tables in the snowflake schema can have their own categories.