How to Optimize Your Relational Database Performance

11 min read
How to Optimize Your Relational Database Performance


Relational databases are the backbone of almost every application we interact with on a daily basis. They store and organize the vast amounts of data that we produce and consume every second of every day. Since we are so dependent on databases, ensuring they are performing at their best is of the utmost importance.

Imagine you’re shopping online, eagerly adding some items to your cart, and just as you’re about to checkout, your internet crashes and the page won’t load. Frustrated, you restart your router and revisit the checkout page, only to find that the e-commerce site is running slower than molasses in the winter. You wait and wait, but the spinning loading icon just won’t go away. Sound familiar? Unfortunately, this exact scenario is far more common than you would expect and is often the result of a poorly optimized database. If your database is running slow, then the user experience and the whole application will suffer, causing frustration for both you and your users.

Fear not! Optimizing your relational database doesn’t have to be a cumbersome or daunting task, once you understand where to start. In this article, we’ll go over why database optimization is important, different performance optimization techniques, and how you can make your database run faster with ScaleGrid. By the end of this article, you’ll have the tools necessary to diagnose bottlenecks and whip your database into shape and enjoy lightning-fast database performance. So let’s get started on your optimization journey!

Why is database performance optimization important?

As technology continues to evolve and becomes more readily accessible, the importance of database performance optimization is becoming increasingly evident. Most applications rely on databases to store and manage large amounts of data. Any degradation in database performance can cause serious issues for the overall performance of your application, ultimately negatively affecting your users’ experience.

Have you ever tried to access a website or use an app only to find that it’s painfully slow or unresponsive? You are likely to quickly grow frustrated and moved on. That user experience is why it’s important to make sure that your database is performing at its best. After all, the database is the foundation of any application and when it’s not working well, your users and the entire application will suffer.

Your database is very much like the engine of your application, and just like an engine, it needs to be serviced and maintained to keep your vehicle performing at its best. If your database performance is slow, your application will be slow as well. Whether you’re running a web app, e-commerce site, social network, or a simple blog, database performance optimization is an absolute must. It’s not just about providing a good user experience, it’s about keeping your application running smoothly and efficiently, so you can avoid downtime, save money, and keep your users wanting to come back.

Types of database performance optimizations

When it comes to optimizing your database, there are several different approaches you should consider. Whether you’re using MySQL or PostgreSQL, there are plenty of ways to tweak and fine-tune your database to get the most out of it. Each of the following optimizations has the potential to improve your database’s performance, and the best way to get the most out of your database is to perform a combination of optimizations.

Query optimization: One of the easiest and most impactful optimization practices you can perform on your database is to optimize your queries. This involves analyzing the way your queries are constructed, looking for any inefficiencies or bottlenecks, and then making changes to improve their performance. A quality performance monitoring solution will provide you with query analysis, allowing you to quickly spot and fix poor-performing queries easily.

Index optimization: Relational database index optimizations involve creating and maintaining indexes on columns in a table that are frequently used in queries, greatly improving query performance by reducing the amount of data that needs to be scanned. By carefully selecting which columns to index and keeping the indexes up-to-date, you can ensure that your queries run efficiently and your database performs optimally.

Disk space management: Effective disk space management includes monitoring and controlling the amount of disk space used by a database to prevent performance degradation and potential data loss. This involves regularly monitoring disk space usage, pruning unnecessary data, and potentially cloning or moving data to larger storage devices. Usually, cloud hosting solutions and managed database services can enable you to scale your storage capacity easily.

Memory optimization: By allocating enough memory to your databases, you can improve their overall performance by reducing disk I/O and increasing the speed of data access. Additionally, caching frequently accessed data in memory can significantly improve performance by reducing the need to retrieve data from disk and paging.

CPU optimization: Your server’s CPU is like the engine that drives it, so make sure it’s beefy enough and optimized for performance. Whether you’re using MySQL or PostgreSQL, there are various ways to optimize your CPU, from adjusting configuration settings to upgrading or migrating.

Connection capacity evaluation: The practice of determining the maximum number of concurrent connections that a database can handle without experiencing depredations in performance. This requires monitoring and analyzing the resource utilization of the database server, such as CPU and memory usage, to identify bottlenecks and ensure that the database has enough resources and capacity to handle the expected workload.

Database clustering: This database structure allows you to scale a database by dividing its data across multiple servers, improving performance and providing high data availability. In a MySQL or PostgreSQL database cluster, multiple servers work together to provide a single, unified view of your data. This distributes the workload of processing and serving data, improving read and write performance and reliability. An added benefit is in the event of a server failure on a primary node, a database cluster can automatically switch to another node, ensuring that your data is always available.

What is a performance monitoring solution?

A database performance monitoring solution is software specifically designed to monitor and analyze the performance of databases, oftentimes in real-time. These monitoring solutions provide valuable insights into database performance metrics and health, such as response times, query optimization, database size, and alerts. With this information, database administrators and developers can quickly identify performance bottlenecks, allocated resources, and resolve issues before they affect the overall performance of the application. By using a database monitoring solution, organizations can ensure their databases are running at their most efficient level, reducing downtime, and improving the overall user experience.

Types of performance monitoring solutions

With a performance monitoring solution in place, you can keep an eye on your database’s performance, identify potential issues before they become bigger problems, and make informed data-driven decisions to improve its performance.

There are many different types of performance monitoring solutions available, from simple, self-hosted solutions to managed cloud-based solutions that can provide real-time monitoring and analysis of resource utilization. When choosing a performance monitoring solution, it’s important to consider your specific needs, budget, and the size of your database. For example, if you’re running a large, complex database, you may want to opt for a more comprehensive managed solution that provides real-time monitoring and advanced analysis capabilities.

Regardless of the type of performance monitoring solution you choose, the benefits of deploying one are clear. With a performance monitoring solution in place, you can take control of your database’s performance, identify areas for improvement, and make data-driven decisions to optimize its performance. Whether you’re a seasoned veteran database administrator or a novice, a performance monitoring solution is a vital tool for optimizing your database’s performance and ensuring that your application remains accessible and responsive for your users.

Features to be on the lookout for include real-time performance monitoring, query analysis, database and server metrics tracking, capacity planning, and alerting.

Server logs

By tracking events such as incoming requests, query execution, and error messages, server logs provide a detailed view of what is happening within your database. These logs can help identify performance bottlenecks and potential security issues. Server logs can also be used to track historical data, allowing you to analyze trends over time and make informed data-driven decisions about potential performance optimizations and resource allocation planning. To view your MySQL or PostgreSQL server logs, you can follow these steps:


  1. Locate the MySQL data directory: The location of the data directory depends on how you installed MySQL, but it’s usually in /var/lib/mysql/.
  2. Find the error log: The error log is named mysql-error.log and it is located in the data directory.
  3. Use the MySQL client: You can use the MySQL client to view the error log by connecting to the database server and running the following command: mysql -u [username] -p. Once you’re logged in, run the command SHOW VARIABLES LIKE 'log_error'; to see the location of the error log.
  4. Use the command line: If you have access to the command line, you can view the error log by using the tail command. For example: tail -f /var/log/mysql-error.log.


  1. Locate the PostgreSQL data directory: The location of the data directory depends on how you installed PostgreSQL, but it’s usually in /usr/local/pgsql/data/.
  2. Find the log file: The log file is named postgresql-{version}-main.log and it is located in the data directory.
  3. Use the PostgreSQL client: You can use the PostgreSQL client to view the log file by connecting to the database server and running the following command: psql -U [username]. Once you’re logged in, run the command SHOW log_directory;. This will show you the location of the log directory.
  4. Use the command line: If you have access to the command line, you can view the log file by using the tail command. For example: tail -f /usr/local/pgsql/data/pg_log/postgresql-{version}-main.log.

Load testing

Simulated heavy workloads help to identify performance bottlenecks, validate scalability, and ensure that the system can handle anticipated levels of traffic and data processing. Load testing is a powerful tool that can be performed on various components of a system, including databases, servers, networks, and applications. Regular load testing can help you better prepare your systems for times of heavy traffic.

Analyze your database server

When you analyze your server, you should keep an eye out for the following potential problem areas: disk space, memory usage, CPU utilization, database query performance, index efficiency, connection capacity, fragmentation of data, network performance, and access patterns. These factors can greatly impact the overall performance of your database and application, for better or worse, so it’s important to stay vigilant and proactively monitor them. What follows is how to address some key performance problem areas.

Disk space

When disk space is low or non-existent, your database may slow down or even crash, which can lead to potential data loss. To address disk space issues, you can consider deleting or moving old or redundant data, using compression and archiving tools, and setting up storage quotas and monitoring systems.

Increase or upgrade memory

To increase memory, you can upgrade your server hardware, add more RAM, or make adjustments to the database’s configuration settings. Additionally, using caching techniques can help reduce the amount of memory your database needs by storing frequently used data in memory.

Strengthen or upgrade CPU

The central processing unit (CPU) is responsible for interpreting computational instructions on your server. To strengthen or upgrade the CPU, you can invest in a more powerful server or upgrade the existing one. You can also optimize your database’s configuration settings to make better use of the available CPU resources.

Optimize queries

Queries are the instructions used to set and get data from a database, and poorly optimized queries can slow down your application, causing performance issues. To optimize queries, you can analyze the database’s query log to identify slow-performing queries and address them. You can also use query optimization techniques, such as indexing, query normalization, and reducing the complexity of queries to improve performance. Read our article on PostgreSQL EXPLAIN Cost and optimize your queries.

Improve indexes

To improve indexes, regularly analyze query performance and identify any underperforming queries. Consider adding indexes to columns used in these queries or updating existing indexes to improve their efficiency.

Connection capacity evaluation

Connection capacity evaluation is the practice of determining how many connections a database can handle at any given time without slowing down or crashing. This is important because a high number of simultaneous connections can put a strain on the database, negatively impacting your application.

Defragment data

Reorganization of data in a database so that related data is stored together, helps improve database performance, as it reduces the amount of time required to search for and retrieve data from disk. Defragmenting data can be implemented through table and index optimization or database compression. This can be automated or performed regularly as part of database maintenance, or on-demand when there is noticeable performance degradation.

Network performance management (NPM)

Network Performance Management (NPM), not to be confused with Node Package Manager, is the process of monitoring, analyzing, and optimizing the performance of network infrastructure to ensure the effective delivery of services and applications. NPM provides measurable insights into network performance issues such as bottlenecks, slowdowns, and failures, and enables IT teams to quickly resolve these issues, improving network reliability and performance.

Review access

This includes reviewing database and user roles and permissions, auditing access control lists, and optimizing database connections. While this is more of a security-related strategy, it can have a direct impact on the up-time of your application.

How to make your database run faster with ScaleGrid

ScaleGrid is a fully-managed database-as-a-service (DBaaS) solution that provides a robust set of tools to enable you to easily deploy, monitor, backup, and scale on a wide variety of hosting platforms. Whether you are running a MySQL or a PostgreSQL database, with ScaleGrid, you can easily increase database performance by allocating additional resources like CPU, memory, and disk space, as well as fine-tuning database configurations, optimizing queries, and improving indexes.


The official MySQL optimization guide: This comprehensive guide provides in-depth information on how to optimize your MySQL database performance. For more information, visit…

The PostgreSQL documentation: This official documentation provides information on how to optimize your PostgreSQL database performance. To learn more, visit…

ScaleGrid’s knowledge base: ScaleGrid provides a wealth of information on database optimization, including tutorials, documentation, best practices, and case studies. Visit

ScaleGrid support: ScaleGrid offers flexible support packages to meet your demands. Whether you’re a small business or an enterprise-level organization, ScaleGrid provides support packages to help you get the most out of your databases. You can find more information about ScaleGrid support packages on the ScaleGrid website:


Database performance optimization doesn’t need to feel overwhelming. Making your database perform well can require a combination of optimization strategies, from analyzing your server to improving or upgrading your memory and CPUs, identifying and optimizing queries, and improving or adding indexes. Regular monitoring and evaluating disk space, connection capacity, and network performance can aid you to maintain proper database hygiene.

ScaleGrid provides a rich set of database optimization tools and knowledgeable support, allowing you to get the most out of your databases, all from a unified dashboard. With ScaleGrid, you can fully reign in your database and ensure that your applications perform at their best. If you’re interested in optimizing your database performance or automating your database processes, check out our website to learn more.

For more information, please visit Connect with ScaleGrid on LinkedIn, X, Facebook, and YouTube.
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