1. Hardware Optimization: Increase your server’s physical resources to handle increased database load. This could include adding more RAM to your server, upgrading your hard drives to SSDs, or adding more CPU cores.
1. Database Indexing: Properly indexing your database can make your query execution faster. Analyze your application’s most frequently used queries and make sure their performance is optimized.
1. Query Optimization: Write efficient and optimized SQL queries. Avoid using wildcards at the start of predicates, avoid null in your database, use limit keywords to prevent large amount of data retrieval, etc.
1. Configuring MariaDB System Variables: MariaDB has many system variables that can be changed to better suit your workload. Variables that commonly receive adjustments are innodb_buffer_pool_size, innodb_log_file_size and key_buffer_size.
1. Use the Latest MariaDB Version: Using the latest stable version of MariaDB ensures that you have all the most recent performance improvements and bug fixes.
1. Partitioning Tables: Partitioning is a method in which a particular table is divided into smaller manageable parts, and thus queries accessing a fraction of the data can run faster because there are fewer data to sift through.
1. Avoid Over-normalization: Over-normalization can cause more CPU load, which can decrease performance. Only normalize what is necessary.
1. Monitor Database Regularly: Use the tools like MONyog, phpMyAdmin, etc., to monitor your MariaDB performance issues and get detailed insights.
1. Caching: Make use of caching mechanisms like Memcached to store frequent DB result sets, so next time if same query requested then it will fetch data from cache instead of hitting DB.
1. Use Persistent Connections: Avoid the overhead of establishing a new connection every time a script has to connect to the database by using persistent connections.
Remember, optimizing a database is experimental most of the time and you must measure your performance before and after each optimization technique applied.
