Types of Schemas

Star Schema

In the star schema design, a single object (the fact table) sits in the middle and is radially connected to other surrounding objects (dimension lookup tables) like a star. Each dimension is represented as a single table. The primary key in each dimension table is related to a forieng key in the fact table.

All measures in the fact table are related to all the dimensions that fact table is related to. In other words, they all have the same level of granularity.

A star schema can be simple or complex. A simple star consists of one fact table; a complex star can have more than one fact table.

Let's look at an example: Assume our data warehouse keeps store sales data, and the different dimensions are time, store, product, and customer. In this case, the figure on the left repesents our star schema. The lines between two tables indicate that there is a primary key / foreign key relationship between the two tables. Note that different dimensions are not related to one another.

Snowflake Schema

The snowflake schema is an extension of the star schema, where each point of the star explodes into more points. In a star schema, each dimension is represented by a single dimensional table, whereas in a snowflake schema, that dimensional table is normalized into multiple lookup tables, each representing a level in the dimensional hierarchy.

For example, the Time Dimension that consists of 2 different hierarchies:

1. Year → Month → Day
2. Week → Day

We will have 4 lookup tables in a snowflake schema: A lookup table for year, a lookup table for month, a lookup table for week, and a lookup table for day. Year is connected to Month, which is then connected to Day. Week is only connected to Day. A sample snowflake schema illustrating the above relationships in the Time Dimension is shown to the right.

The main advantage of the snowflake schema is the improvement in query performance due to minimized disk storage requirements and joining smaller lookup tables. The main disadvantage of the snowflake schema is the additional maintenance efforts needed due to the increase number of lookup tables. 

Galaxy Schema:

Galaxy schema contains many fact tables with some common dimensions (conformed dimensions). This schema is a combination of many data marts.

Fact Constellation Schema:

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 teritary, region, country, state and city; constellation schema would have five dimensions instead of one.