Replacing traditional joins with in-memory dictionaries in ClickHouse Cloud can significantly enhance query performance and reduce costs with minimal SQL modifications. By utilizing ClickHouse-native dictionaries for dimension table lookups, users can achieve up to 6.6 times faster query execution and over 60% cost savings, as demonstrated in benchmark tests involving 1.4 billion rows. This approach leverages the high-speed, low-latency advantages of in-memory key-value structures, making it particularly effective for foreign key joins on small dimension tables in star or snowflake schemas. The transition from joins to dictionaries is seamless, requiring no data reloading or schema changes, and scales efficiently across multiple compute nodes. This method not only optimizes execution times for complex queries but also highlights the adaptability and power of the ClickHouse engine, encouraging users to consider its cloud services for enhanced performance and cost efficiency.