Data is the basic unit of any information transaction today. This includes everything present on the internet and off it. Large organizations have seen an exponential growth in their data network. This has increased the load on database systems. But, how to these database system cope up with the load?
Optimization is the key to the smooth functioning of any database system. But before we delve deeper, let’s understand what database optimization is. And more. importantly, why do we need database optimization?
As the data increase, the load on the system increases. This results in a degraded system performance often leading to slower response times. The process of tweaking the system to avoid any delays and increase response time is known as database optimization. The process of database optimization aims to maximize resource usage while minimizing idle time.
How to optimize database performance?
But the more important question is how to optimize database performance? There are several key practices which are important for any database optimization process. These best practices include:
An index is used to retrieve data in clusters of the database. While data can be retrieved without an index as well, indexing speeds up the process. But, even with indexes, it is important to find balance. Too much or too little will lead to a slow performing database.
Coding loops often leave the system slowed down. To overcome this problem, we need to avoid coding loops through the use of UPDATE or INSERT commands. This helps avoid updating stored data. Whenever the command WHERE is used, it ensures that pre-pre-existing data, if matched, is not updated.
Temporary tables are often used in cases with multiple queries. There are also times when the user needs to select between temporary tables or sub-queries. To optimize the database performance it is necessary to understand the use of the two and act according to the one that offers maximum performance. Also, avoiding temporary tables in certain cases is important.
Limit data retrieval
By limiting data retrieval, the user specifically retrieves selected data. This causes quicker retrieval without any additional time or data. When tuning a database, instead of SELECT*, using a LIMIT (for data from specific rows) or * (while retrieving data from specific columns) command optimizes the performance. In addition, rather than retrieving the entire data, select data retrieval will add to the performance.
The most important component for any database is a query. A query performs the actions in a database. To optimize a database, it is important to optimize a query. Because without an optimized query chance of a well-performing database are less.
Why is database optimization necessary?
Let us take a simple example. The data stored in a database is in the form of files. Whenever a query is executed to delete data of any form stored in the database, the system deletes the information. But, even after deletion, the file remains with an empty space. This empty space takes up some space in the database. Similarly, when multiple files with empty spaces are left in the system, the database performance is affected.
Similarly, as previously mentioned, there are times when executed queries fetch data for the user. The specification of this data plays an important role because unnecessary retrieval of data will affect the speed. This causes a delay in the response time.
Thus, To avoid such situations as well as excessive load on the database and to speed up the processing, it is very important to regularly optimize the database. Database optimization is extremely important for all operations of any organization in the present day. Any issue with data management can be lethal for the system.