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Difference between Star Schema & Snow Flake Schema?
In general way if we say
1.When you have one Fact Table and Multiple Dimension Tables is a Star schema.
2.When You have a Fact Table it is connected to dimension table and then sub dimension table is a snow flake schema.
Here are the main difference from the learning website
Snowflake Schema | Star Schema | |
---|---|---|
Ease of maintenance / change | No redundancy and hence more easy to maintain and change | Has redundant data and hence less easy to maintain/change |
Ease of Use | More complex queries and hence less easy to understand | Less complex queries and easy to understand |
Query Performance | More foreign keys-and hence more query execution time | Less no. of foreign keys and hence lesser query execution time |
Type of Datawarehouse | Good to use for datawarehouse core to simplify complex relationships (many:many) | Good for datamarts with simple relationships (1:1 or 1:many) |
Joins | Higher number of Joins | Fewer Joins |
Dimension table | It may have more than one dimension table for each dimension | Contains only single dimension table for each dimension |
When to use | When dimension table is relatively big in size, snowflaking is better as it reduces space. | When dimension table contains less number of rows, we can go for Star schema. |
Normalization/ De-Normalization | Dimension Tables are in Normalized form but Fact Table is still in De-Normalized form | Both Dimension and Fact Tables are in De-Normalized form |
Data model | Bottom up approach | Top down approach |
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