There are four types of schemas are available in data warehouse. Out of which the star schema is mostly used in the data warehouse designs. The second mostly used data warehouse schema is snow flake schema. We will see about these schemas in detail.
A star schema is the one in which a central fact table is surrounded by de-normalized dimensional tables. A star schema can be simple or complex. A simple star schema consists of one fact table where as a complex star schema have more than one fact table.
A snow flake schema is an enhancement of star schema by adding additional dimensions. Snow flake schema are useful when there are low cardinality attributes in the dimensions.
Galaxy schema contains many fact tables with some common dimensions (conformed dimensions). This schema is a combination of many data marts.
The dimensions in this schema are segregated into independent dimensions based on the levels of hierarchy. For example, if geography has five levels of hierarchy like territory, region, country, state and city; constellation schema would have five dimensions instead of one.