Replicated table is a great fit for small dimension tables in a star schema with less than 2 GB of storage after compression

A replicated table is indeed an excellent choice for small dimension tables within a star schema, especially when the dimensions involved are relatively small—typically less than 2 GB after compression.

1. Efficiency: In a star schema, dimension tables are often joined with fact tables to enable analytical queries. Replicating small dimensions across multiple nodes can significantly accelerate query performance, as it reduces the need for distributed join operations.

2. Simplicity: With smaller dimension tables stored locally on each node, queries can access needed data without network overhead. This leads to simpler query planning and execution, which optimizes overall performance.

3. Cost-Effectiveness: Since replicated tables eliminate the need for complex join operations in distributed environments, they help reduce computational costs, making them a cost-effective option for organizations dealing with large volumes of data but relatively small dimensions.

4. Scalability: While replication works best for small dimension tables, it's important to evaluate its impact on scalability. If dimension tables grow beyond the 2 GB threshold, alternative strategies (like partitioning) may need to be considered.

In summary, replicated tables are advantageous for small dimensions in a star schema context due to improved performance, reduced complexity, and potential cost savings. However, careful consideration should be given to size limits and scalability as needs evolve.