One commonly used SQL optimization technique is creating indexes on frequently queried columns, as this helps improve search performance by reducing the number of rows that need to be scanned. Another technique is optimizing the query structure by avoiding unnecessary joins, subqueries, or complex expressions. Additionally, using appropriate data types and defining constraints can also enhance performance. Caching query results, implementing denormalization for frequently accessed data, and using query hints or optimizer directives are other techniques to consider.

Besides the techniques discussed, consider exploring database performance monitoring and tuning tools. These tools provide insights into query performance by tracking metrics like execution time, disk I/O, and CPU usage. By monitoring these metrics, you can identify performance bottlenecks and make targeted optimizations. Another technique is materialized views, which are precomputed result sets stored as physical tables. Materialized views can significantly improve query performance for complex or frequently executed queries. Lastly, adopting query rewriting frameworks or technologies that automatically optimize SQL queries based on predetermined patterns or rules can also be beneficial.

In addition to the techniques mentioned earlier, using partitioning can help improve query performance. Partitioning involves dividing large tables into smaller, more manageable chunks based on specific criteria, such as range or list partitioning. This can speed up queries that only need to access a subset of the data. Another technique is query rewrite, where you identify and rewrite queries to use more efficient alternative syntax or constructs. Vertical and horizontal scaling can also be considered by adding more resources or distributing the workload across multiple servers.

Apart from the techniques already mentioned, you can explore query optimization using query plans. This involves analyzing the execution plan generated by the database optimizer for a specific query and identifying potential bottlenecks or inefficiencies. By understanding the execution plan, you can make informed decisions about refactoring queries, creating appropriate indexes, or rewriting queries. Additionally, using query tuning tools or profiler utilities provided by your database system can help identify and optimize expensive or long-running queries. Query optimization is an ongoing process, as new data, schemas, or requirements may necessitate further tuning.