Migrating to distributed SQL can significantly enhance relational database performance by addressing common optimization challenges, primarily focusing on query efficiency. Optimizing queries involves identifying computationally expensive queries using tools like EXPLAIN ANALYZE to understand execution details and implementing best practices such as creating indexes, using specific SELECT statements, and opting for INNER JOINs over OUTER JOINs. Indexes are vital for reducing query execution times, though they should be used judiciously to avoid negatively impacting write performance. Optimizing database schema, such as selecting appropriate data types, can also contribute to improved performance. Each relational database management system (RDBMS) has unique characteristics, and understanding these can inform the best optimization strategies. For instance, while sequential IDs might suit legacy systems, they may hinder performance in distributed databases like CockroachDB, which benefits from multi-region deployments to reduce latency. Overall, the optimization approach requires a balance between query performance, schema design, and understanding the specific requirements of the RDBMS in use.