Database optimization is the strategy of reducing database system response time.
Databases provide us with information stored with a hierarchical and related structure, which allows us to extract the content and arrange it easily. There are plenty of options to choose from for business and companies. Even though MySQL is the most widespread database, there are other alternatives, such as Microsoft SQL Server, PostgreSQL, or MongoDB.
Regardless of our choice, there are a number of common recommendations regarding the management and optimization of the databases. Following these best practices will make your work easier, improving the experience of our users.
How to Practice Database Optimization
1. Avoid Unused Tables
No matter how carefully you plan the initial approach to the database, as time goes by, you inevitably end up with unused tables. Just do not hesitate: delete them! Having unused tables is quite similar to keeping things you don’t use in a full drawer. When you go looking for something, it can take you much longer to find it! The same thing happens in the databases: the systems have to track all the tables and elements until they find the answer to the query.
2. Proper Indexing
Having a good index among tables is essential for relational searches to work correctly. Add indexes to the tables and use the query statements (SELECT, WHERE …). It is also advisable to periodically check the registry of slow queries to identify those that should be optimized. No indexing at all or excessive indexing are not a good idea. Without any indexing, the process will be prolonged, whereas indexing everything will render the insert and update triggers ineffective
3. Avoid Temporary Tables and Coding Loops
If any a code can be well written simply, there is absolutely no need to make it complex with temporary tables. Subqueries usually alternate temporary tables, but keep in mind the precise performance that each of these would provide in each case.
Avoiding coding loops is much required in order to prevent stalling the entire sequence. It can be accomplished by employing the unique UPDATE or INSERT commands with individual rows and by making sure that the WHERE command does not update the stored data in case it finds a preexisting matching data.
Of course, there are many other ways to tune your SQL database in the most efficient and practical way. Moreover, there is a big likelihood that the steps mentioned in this article might not be the appropriate choice for all databases, as each database will require optimizing techniques uniquely specific to its needs.
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