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How To Optimize Database Performance: Best Practices


MySQL and PostgreSQL are the two most popular database management systems (DBMS) worldwide. MySQL, an open-source software, features reliability, a user-friendly interface, and exceptional efficiency. In its turn, PostgreSQL is a robust open-source DBMS that offers a comprehensive set of features and functionalities for developing complex applications. To effectively optimize database operations, it is crucial to understand the structures of DBMSs, this knowledge will enable you to identify areas for improvement and implement necessary enhancements within the system.

Operation Principles And Mechanisms Of DBMSs

Any DBMS is based on a so-called database engine. It processes requests, interacts with data, and stores it. The engine uses various algorithms to do that:

  1. Indexing. One of the main mechanisms speeding up data access. An index is a data structure that allows the DBMS to quickly find rows in a table without having to look through each of them.
  2. Buffering. Most DBMSs use a memory buffer to temporarily store frequently used data, which reduces the access time.
  3. Query Optimizer. This component analyzes database queries and determines the most efficient way to execute them.
  4. Transactions. DBMSs use the transaction mechanism to ensure data integrity and provide consistency control means for simultaneous access by several users.

Optimization Necessity

As data volumes grow, database efficiency may decrease. An unoptimized DBMS can become a problem in system operation, leading to delays and loss of performance.

Database optimization improves the basic characteristics of the system and the user experience, so it is necessary to perform it on a regular basis.

Internal Optimization

Excessive index creation can slow down data insertion, updating, and deletion processes within the database. It is important to create indexes on columns that are frequently used in query conditions.

Customizing memory settings, such as buffer and cache sizes, can have a significant impact on performance.

Query optimization

  1. Using the Explain Query Plan (EXPLAIN) command line, you can examine how the MySQL server processes queries, identifying which indexes are involved or ignored.
  2. Avoiding correlated subqueries and using JOIN instead of multiple joins are two strategies for optimizing joins and subqueries.

MySQL Database Optimization

MySQL provides profilers to track query execution time at various stages, assisting in the identification of problematic areas. Monitoring server performance, including CPU usage, RAM usage, and disk space, is also essential. Tools for monitoring and optimizing MySQL are available to help detect problems.

PostgreSQL Optimization

Let's take a look at the key aspects of PostgreSQL optimization.

Internal Optimization

Transaction management in PostgreSQL is carried out using the MVCC system, which allows multiple transactions to safely run in parallel. Long-running transactions, on the other hand, can result in an accumulation of dead rows. While it’s possible to do this manually, you might need some tools to delete them.

Consider optimizing system performance through the use of various index types such as B-tree indexes. Additionally, optional index structures such as GiST, GIN, and SP-GiST can be used to improve system performance.

External Optimization

The command ANALYZE will help you obtain statistics based on the table.

Optimize JOINs and subqueries. Use LEFT JOIN only if it is really necessary.

PostgreSQL Efficiency Optimization

  1. Using monitoring tools: there are many tools for monitoring PostgreSQL, such as pg_stat_statements or pgBadger, that can help you identify bottlenecks in DBMS performance.
  2. Server configuration: special attention should be paid to configuration parameters such as shared_buffers, work_mem, or maintenance_work_mem to ensure optimal performance.


Tips for optimizing your database require long-term planning, strategic thinking, and a dedication to continuous learning. Here are the main components that ensure you implement best practices:

  1. Data Planning: Keep in mind the potential for growth and change.
  2. Regular Testing: Periodically test your system to identify and address problems.
  3. Security Measures: Utilize various features to enhance the security of your system.
  4. Continuous Learning: Engage in ongoing learning and explore new aspects of the field.

Key Nuances

Understanding how DBMS works helps you set up and improve your system accurately. When you plan your data structure with future needs in mind, you can prevent many performance issues in advance. It's essential to regularly make your database work better to find problems and check if changes are effective. Protecting your data is very important. So, think of optimizing your database as an ongoing task that needs attention, time, and resources. Even though it requires effort, investing in this process ensures your database performs much better, is more reliable, and keeps your data secure. Don't hesitate to try out new things and explore different practices.

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