Are there any advantages to not nullable columns in redshift?

Yes, there are advantages to using NOT NULL columns in Amazon Redshift, beyond the sortkey feature you mentioned.

1. Data integrity: NOT NULL constraints enforce data quality by ensuring that essential columns always contain a value. This helps maintain the consistency and reliability of your data.

2. Query optimization: The query planner can make better optimization decisions when it knows a column will always contain a value. This can potentially lead to more efficient query execution plans.

3. Storage efficiency: Redshift can optimize storage for NOT NULL columns, potentially reducing the overall storage footprint of your table.

4. Improved statistics: When Redshift generates statistics for query optimization, NOT NULL columns provide more accurate and useful information, which can lead to better query performance.

In your specific case, if the date column is always populated, marking it as NOT NULL would align the table definition with the actual data characteristics. This can provide the benefits mentioned above, particularly in terms of query optimization and statistics generation.

While recreating the table might seem like an extra step, the long-term benefits in terms of query performance and data integrity could outweigh the short-term effort, especially for frequently accessed or large tables. However, the decision should be based on your specific use case, considering factors such as the table size, query patterns, and the impact of table recreation on your workflows.
Sources
Table constraints - Amazon Redshift
Sort keys - Amazon Redshift