By refactoring certain specific code, already in production, and starting to apply Best Practices when developing in SQL Server, we are looking to enhance our management capacity to increase current performance. Preventing “bottlenecks” and anticipating issues that may subsequently lead to high development and resource costs is also necessary.
Best programming practices for relational databases
Applying Best Practices will also allow us to reduce programmer development times. The code will become more efficient and different programmers will be able to reuse, understand and improve it, since certain decisions can be implemented in a standardized manner and will facilitate teamwork. The work of a developer who needs to maintain code created by someone else will be much easier.
A database system’s performance depends on multiple factors, making it difficult to guarantee that actual performance improvements will match predictions. Optimization is mostly a craft that must be system-wide, but the most radical improvements are usually found by solving and refactoring poor database code.
Creating a database schema and “future proof” code isn’t easy for anyone. The requirements at the start of our business are very different from when we have been operating for many years. The success of the company also brings expansion into different geographies and a growth in data volume. This means that some of the solutions that need to be created temporarily and urgently can be made permanent, as can a lot of “custom code” for the occasion.
There are numerous reasons for poor coding and most of the time it is because the developer who is writing the code is not fully familiar with the database scheme or the new Transact-SQL features. In any case, having a good knowledge of the Data Model can only bring us huge benefits and advantages. Therefore, our first and mandatory Best Practice should be to master our database model.
There are many database schematic design malpractices. However, we almost always only find them after the business has become successful. And then, after a while, it becomes difficult to change said scheme. Therefore, decisions on the database model should never be made “lightly”.
By gathering information about an application and how it is used, we can make intelligent architecture decisions that will ensure our database is more scalable and works better over time. Ultimately this will produce better performance, and we are less likely to have to waste time solving problems later.
In coming articles, we will continue to discuss the big benefits of applying Best Practices already implemented in Teldat for our developments in SQL Server Databases in the cloud.