Caching frequently accessed query results using temporary tables or materialized views can also improve performance by reducing the need for redundant computations.

One way to optimize queries is by analyzing the query execution plan using EXPLAIN or EXPLAIN ANALYZE. This helps in identifying bottlenecks and optimizing the query structure or applying appropriate indexes.

Another approach is to use appropriate indexing techniques such as B-trees or hash indexes based on the type of data and the query requirements. Indexing can significantly speed up query performance.

Partitioning large tables based on a chosen criteria can also enhance performance. It allows for distributing data across multiple physical files or storage systems, reducing the time taken for data retrieval.

Properly structuring database schema by normalizing tables and avoiding redundant data can make queries more efficient.