Database Optimization is a necessary process for any enterprise application. It’s an ongoing process throughout the life cycle of an application. Optimization aims to keep database performance at an optimum level as data, load, and operations increase. From reviewing indexing strategies to changing SQL queries to changing the database structure itself come under the umbrella of Database Optimization.
These tasks are often critical as mistakes can cause many performance issues or even service loss. Thus, it becomes imperative for DBAs and developers to follow specific guidelines and refer to the best practices. The steps that are taken to execute the tasks correctly ensure errors are minimized drastically. We have been optimizing databases for over two decades, and in this article, we will share some tips to learn or incorporate when you are working with a database and optimizing it.
Database Optimization Tips
The following tips apply to almost all the stakeholders in an application’s development and support life cycle. They consist of best practices, regions where DBAs are required, and scenarios where they aren’t.
1. Create and Maintain Multiple Database Environments
Database issues can come anytime. Even with a thoroughly tested database server, there can be some unforeseen scenarios that can cause trouble. Thus it becomes imperative that the application has several database environments deployed where issues can be replicated, upgrades can be tested, and test suites can be executed.
The ideal scenario is where three database environments can be set up. They are:
- The development environment
- The staging environment
- The production environment
The
production environment will be present for all applications. However, the other two environments’ availability is subject to many factors, including a financial budget, teams to maintain it, or sometimes even the lack of knowledge. Having two or all the three environments helps
database administrators and developers with the development, testing, and support processes and keeps the production database reliable. These environments will help tremendously with quality assurance processes as well.
2. Production Database Server Changes
When issues arise in a production environment, a DBA does not directly change the production server. It’s a highly unusual scenario. The correct way is to replicate the issue in the staging or development environment, fix and test the solution, and only then apply it to the
production database server. Making changes directly to the production server can cause severe issues either immediately or in the future, causing much more damage than expected.
Getting access to make changes to database tables in the production environment is also highly unusual. Data corruption can cause a domino effect, which might nor even be detected until it’s too late. A DBA has to be sure that there is no other possible way to perform the changes before embarking on the production server modifications.
3. Planning of Data Migration
None of the most widely used databases like
MySQL, Oracle Database, etc.. have remained the same. As technologies improve, database creators upgrade their databases or fix some critical issues in the newer versions. Most organizations don’t plan for migrating their data to the newer DB versions, or they tend to reject it as it wasn’t in their plan.
We often see organizations forced to perform an upgrade because of loss of support or the older database version not meeting their expectations. The best thing to do here is accept that data migration is a necessary and unavoidable task and plan for it. So, when the time comes, the DBA and their team are ready for it.
4. Speed of Database Optimization Processes
Database optimization is one of the
primary functions of a DBA. It involves a series of tasks carefully executed to achieve desired performance goals or identify threats. These tasks include analyzing the database structure, identifying slow queries, optimizing queries to improve performance, recommending the best indexing strategies, and more. Given the size of databases, these tasks take time to be done correctly.
The optimization process is not all about recommendations, either. DBAs must test and analyze the impact of recommendations as well. They would have to explore possible side effects in resource utilization, cost increase or reduction, and even performance gains. Since the entire application rests on the database’s reliability, these tasks are executed thoroughly, and they take time to complete.
Organizations should ensure that the DBAs and their teams are not rushed to complete these tasks. It often happens that organizations bring in a team of database administrators when there is a crisis, and they will be under tremendous pressure to solve the issue quickly. This can be avoided by planning for database optimization tasks and providing the team with ample time to ensure everything is in order.
5. Database Design Changes
Enterprise Applications never stay static. The requirements, design, and functionality frequently change with time. This also means that the database must support any given changes that may arise from these newer requirements. As DBAs, we need to ensure that the database stays as flexible as possible to incorporate changes easily.
The flexibility of a database can be achieved in various ways. Normalization of databases, the ability to store dynamic data, and even choosing the NoSQL approach for some of the data points are examples for maintaining flexibility. Flexibility also allows for rapid changes to be made in specific scenarios until an appropriate solution is implemented.
6. Handling Application Issues
Applications have issues all the time, but database related problems causing them are not the primary reason. Databases rarely die out or give up suddenly. They show signs of trouble like slow queries, long response times, or even notifications of strained hardware. These bottlenecks and warnings can be caught quickly and usually and seldom occur out of nowhere. So, application developers can be advised to look at other application parameters before engaging the DB developers or DBAs to look for database faults potentially.
On the other hand, databases such as
MySQL, SQL Server, etc. come with tremendous monitoring and reporting capabilities. Database administrators can create a dashboard to show key real-time statistics about database server metrics and performance metrics. If such a dashboard has been set up and shared with the application developers, they can quickly glance and confirm if the problem arises from the database or the application server.
7. Adopting a Hybrid Approach
As of today, the decision is no longer to choose between a relational and a NoSQL database. The types of data handled by a database vary significantly, and DBAs and DB developers need to consider that while designing the database. The goal must be to ensure the most efficient way to store and retrieve the data. If this requires a combination of the two types of databases, then it must be adopted.
User-generated data such as product reviews, and chats, do not have any particular structure. However, the users themselves have some standard information that the application gathers. Scenarios like these use hybrid approaches to make the best of both worlds.
Conclusion
The tips and best practices we have looked at apply to various actors in a software development lifecycle. From developers to managers and key decision-makers, it’s essential to realize that database optimization is a vast and complicated task. It requires skill, time, and experience to ensure the best results.
These guidelines do not cover all the topics, but we have covered the most important ones. Having these recommendations in place ensures that the database is reliable, and optimizations can be carried out without significant issues.
