Is a Star-Schema design essential to a data warehouse? Or can you do data warehousing with another design pattern?
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The thing about star schemas is they are a natural model for the kinds of things most people want to do with a data warehouse. For instance it is easy to produce reports with different levels of granularity (month or day or year for example). It is also efficient to insert typical business data into a star schema, again a common and important feature of a data warehouse.
You certainly can use any kind of database you want but unless you know your business domain very well it is likely that your reports will not run as efficiently as they could if you had used a star schema.
Star schema is a logical data model for relational databases that fits the regular data warehousing needs; if the relational environment is given, a star or a snowflake schema will be a good design pattern, hard-wired in lots of DW design methodologies.
There are however other than relational database engines too, and they can be used for efficient data warehousing. Multidimensional storage engines might be very fast for OLAP tasks (TM1 eg.); we can not apply star schema design in this case. Other examples requiring special logical models include XML databases or column-oriented databases (eg. the experimental C-store)).