Reduced query execution time: Optimized databases can retrieve data much faster, leading to quicker response times for applications and users.

Lower resource consumption: Simplified queries use fewer resources such as CPU, memory, and disk I/O, which can improve the overall performance of the database server.

Reduced data redundancy: Data consistency and integrity can be enhanced by removing redundant data, which can be accomplished with the aid of optimization techniques like normalization.

Buffer Tuning: Adjust buffer sizes for key areas like query cache, InnoDB buffer pool, and sort buffer to optimize memory usage and minimize disk access. 

Thread Pool Management: Configure thread pool settings like innodb_thread_concurrency and max_connections based on workload and hardware resources to avoid thread starvation and optimize concurrency.

Resource Limits and Tuning: Set appropriate limits for memory usage, connections, and temporary tables to prevent resource exhaustion and ensure efficient server operation.

Web Server Optimization: Tune web server settings like thread pool size, caching mechanisms, and compression to handle concurrent requests efficiently.

Application-Level Profiling: Use profiling tools to identify performance bottlenecks within your application code and address them through code optimization techniques.

Caching Mechanisms: Implement caching layers for frequently accessed data to reduce database load and improve application responsiveness. Consider in-memory caches like Redis or Memcached.