Difference between Star Schema and Snowflake Schema
Star Schema: Star schema is the type of multidimensional model which is used for data warehouse. In star schema, The fact tables and the dimension tables are contained. In this schema fewer foreign-key join is used. This schema forms a star with fact table and dimension tables.
Snowflake Schema: Snowflake Schema is also the type of multidimensional model which is used for data warehouse. In snowflake schema, The fact tables, dimension tables as well as sub dimension tables are contained. This schema forms a snowflake with fact tables, dimension tables as well as sub-dimension tables.
Let’s see the difference between Star and Snowflake Schema:
||In star schema, The fact tables and the dimension tables are contained.
||While in snowflake schema, The fact tables, dimension tables as well as sub dimension tables are contained.
||Star schema is a top-down model.
||While it is a bottom-up model.
||Star schema uses more space.
||While it uses less space.
||It takes less time for the execution of queries.
||While it takes more time than star schema for the execution of queries.
||In star schema, Normalization is not used.
||While in this, Both normalization and denormalization are used.
||It’s design is very simple.
||While it’s design is complex.
||The query complexity of star schema is low.
||While the query complexity of snowflake schema is higher than star schema.
||It’s understanding is very simple.
||While it’s understanding is difficult.
||It has less number of foreign keys.
||While it has more number of foreign keys.
||It has high data redundancy.
||While it has low data redundancy.
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