As you are looking for SQL DB optimization methods, you may know what SQL means. In a nutshell, the full form of SQL is Structured Query Language. Thus, it is a language that is structured and used to query the database or help programmers to communicate with the database. So, SQL is the database communicator that is written in simple English language for the execution of different tasks like updating, inserting, or retrieving data.

In most IT organizations, the teams are understaffed which results in overloading of work because of handling various issues of the distributed IT environment. One of the most critical components is the database that needs to be managed and monitored. Hence, SQL DB optimization is much crucial. Therefore, in this article, we will point out the top 5 ways to optimize your SQL database.

A database with a good design helps in improving database performance because that will help to run the SQL queries faster. It is highly mandatory to be aware of the database optimization techniques because a small delay can also result in bigger issues.

So, stay tuned to get various tips for SQL performance tuning!

Best 5 Ways to optimize your SQL database

In this section, we will take you through the major 5 tips for SQL performance tuning or database optimization techniques. They are:

• Optimal and perfect indexing
• Allocation of more memory and stronger processor
• Avoiding correlated queries
• Query optimization
• Retrieving relevant data.

Let’s take a look at them in detail now.

Optimal and Perfect Indexing

The index is usually a type of data structure that helps in faster data retrieval. Doing proper indexing can help in improving database performance overall by optimizing the total duration of query execution. Indexing structures the data and organizes them in such a fashion that locating data becomes a lot easier.

Hence, implementing proper and optimal indexing can increase efficiency and SQL DB optimization. But, no indexing and excessive indexing can hamper the database performance overall. Without any indexing, the data retrieval process will be slow while excessive indexing can cause the inserting and updating triggers to become ineffective.

Allocation of more memory and stronger processor

CPU performance is directly related to SQL DB optimization. If the CPU is better, then the database will be highly efficient. So, in case of any database performance issues, consider upgrading your CPU to the next level. Installing a more powerful CPU can help to handle multiple tasks simultaneously. It’s one of the straight-forward database optimization techniques.

Like the CPU performance, lack of memory also needs to be considered if the database underperforms. Ensure that your system has more memory available as that will help to boost the overall system’s efficiency and performance. You can keep track of the memory by checking the page faults. The page faults being higher imply that the hosts are running low on memory.

Hence, if the database performance has degraded anytime, try to upgrade the CPU or allocate more memory.

Avoiding correlated sub-queries

Using excessive correlated sub-queries can decrease the overall database performance. Correlated sub-queries mean there is a parent query that is using other child queries to meet a specific condition. This type of search is usually done row by row, thereby decreasing the overall speed.

With the use of more correlated sub-queries, the time taken will be more and the overall database efficiency will be hampered. So, it’s better to avoid correlated sub-queries as much as possible and instead use joins there. However, some places are there that make it mandatory to use correlated sub-queries.

Query optimization

As you know, SQL is used to query the database for the execution of certain operations. For that, you need to write SQL statements or queries with various conditions, joins, and more. Optimizing those queries is one of the best database optimizations techniques. Can you guess why!

It’s because good query optimization will require lesser time to query the database or perform the operation thus enhancing the SQL DB performance. There are various strategies to know how well you can optimize the queries. One has already been discussed in the previous point where we recommended you to use joins instead of correlated sub-queries wherever possible.

Coding loops must also be avoided to prevent the entire process to slow down. Also, if the code can be written simply, then you must not use temporary tables. However, some cases do require you to include all these but make sure about the time complexity. Always try to use specific methods so that the time complexity of the queries can be made lower.

Now, you may face confusion or run into dilemmas a lot of time while optimizing the queries. Hence, it’s better to use the query optimization tools available online so that you can save both time and effort.

Retrieving relevant data

People generally need only a certain part of data at a time but they tend to retrieve the entire data from the database by using ‘Select *.’ This should be avoided when the data set is very huge as that can impact the overall database performance and can cause the database to go into a hung state as well sometimes. So, always use specific conditions, keywords to filter out the data and get only the portion that you need.

It is not necessary when the data contained in the database is less but this should be taken care of while assessing the data from a larger source. This is not a necessary rule but it can be done to avoid system errors in the future and keep your database healthy.

Final Words…

We hope that you have found this article on the top 5 ways to optimize your SQL database quite helpful and informative. All these tips for SQL performance tuning are checked on a real-time basis before including them here. So, you must strictly follow them to keep the database in good health.

There are many other ways to tune your SQL DB performance but the ways mentioned above are the best ones.

You can check out this detailed guide on SQL Query Optimization