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maniram23
Creator II
Creator II

star & snowflake schema

hi friends,

what is star schema and snowflake schema. what are the differences?

8 Replies
arulsettu
Master III
Master III

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.

robert_mika
Master III
Master III

One link of many

diffen.com/difference/Snowflake_Schema_vs_Star_Schema

In your data model try use star schema as often as possible.

Snowflake schema is an extension of the star schema, where each point of the star explodes into more points.

It will be harder to read and understand your model

prma7799
Master III
Master III

Not applicable

Star Schema

  • Each dimension in a star schema is represented with only one-dimension table.
  • This dimension table contains the set of attributes.
  • The following diagram shows the sales data of a company with respect to the four dimensions, namely time, item, branch, and location.
  • There is a fact table at the center. It contains the keys to each of four dimensions.
  • The fact table also contains the attributes, namely dollars sold and units sold.





Snowflake Schema

  • Some dimension tables in the Snowflake schema are normalized.
  • The normalization splits up the data into additional tables.
  • Unlike Star schema, the dimensions table in a snowflake schema are normalized. For example, the item dimension table in star schema is normalized and split into two dimension tables, namely item and supplier table.
robert_mika
Master III
Master III

The following diagram shows .....

?

Not applicable

Description

Star Schema

Snow Flake 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

Regards

Harsha Nandan

pratap6699
Creator
Creator

STAR schema::one central fact table connected to multiple dimension tables is star.

SNOWFLAKE::it is extension of star,one fact table connected to multiple dimensions with sub dimesion tables this is called snowflake ...if possible try for make snowflake to star because star is very user friendly more understanding manner and star contain less joins so performance is good than snowflake.

ankitaag
Partner - Creator III
Partner - Creator III

Hi,

Start schema is where a fact table is directly linked with multiple denormalised dimension tables.

Star.PNG

Snowflake scheema is where a fact table is dirctly or indirectly linked with normalised dimension tables. (dimension tables are linked with other dimension tables)

snowflake.PNG

Thanbks and Regards,

Ankita