What is the difference between snow flake and star schema

Star Schema	Snow Flake Schema
The star schema is the simplest data warehouse scheme.	Snowflake schema is a more complex data warehouse model than a star schema.
In star schema each of the dimensions is represented in a single table .It should not have any hierarchies between dims.	In snow flake schema at least one hierarchy should exists between dimension tables.
It contains a fact table surrounded by dimension tables. If the dimensions are de-normalized, we say it is a star schema design.	It contains a fact table surrounded by dimension tables. If a dimension is normalized, we say it is a snow flaked design.
In star schema only one join establishes the relationship between the fact table and any one of the dimension tables.	In snow flake schema since there is relationship between the dimensions tables it has to do many joins to fetch the data.
A star schema optimizes the performance by keeping queries simple and providing fast response time. All the information about the each level is stored in one row.	Snowflake schemas normalize dimensions to eliminated redundancy. The result is more complex queries and reduced query performance.
It is called a star schema because the diagram resembles a star.	It is called a snowflake schema because the diagram resembles a snowflake.