Can Teradata support star schemas?

Teradata has handled "star" and "snowflake" joins for a long time. Often, the optimizer will build a plan that initiates a product join among several dimension tables after qualifying them and then redistributing the result so it can easily join the large fact table. Teradata customers, especially those in retail, have used this technique very effectively since 1988.
Snowflake joins occur when star tables are joined to other tables in the query. Some of those joins can reduce the cardinality of the star tables. The optimizer recognizes joins that reduce cardinality and executes them prior to performing the product join, resulting in fewer rows and, thus, a shorter merge join phase. The algorithm is sophisticated enough to recognize multiple star joins in a single query and to recognize when one of the star joins is a snowflake of another.
Most Teradata optimizations for star joins rely on a large fact table with a composite primary index of columns that are the equi-join fields for the dimension tables. All of the dimension tables with a join field included in the primary index must be included in the star join. This allows the optimizer to join the dimension tables to produce the composite primary index and thus execute a high-performing merge join known as a "row hash match scan."

Teradata is very good at dealing with queries that do not fit a pattern, no matter what the underlying physical model. You won't limit the type of queries you can ask by using dimensional modeling in your Teradata system. The Teradata optimizer can build an optimal plan for any query involving the tables, regardless of whether it fits the star join conventions.

For this reason, and because the Teradata optimizer is good at delivering on complex requests, and additionally because many users have found it easier to add subject areas using a third normal form model, a normalized schema is often recommended. In addition, many users find it easier to add subject areas with a normalized model. This recommendation is often misinterpreted to mean that third normal form is required with Teradata, when in fact the Teradata technology is completely neutral when it comes to the data model.