In the web world, we know that faster websites tend to rank higher on search results and provide a better user experience. Good user experience and more reach, in turn, results in high conversion rates and more revenue. No wonder modern-day website owners want to achieve faster page loading speed as a default development objective.
In terms of improving website speed and performance, database optimization plays a vital role. The developers who normalize a relational database try to restructure the DB to reduce any data redundancy to increase the data integrity and, ultimately, the speed. However, there are times when normalizing a database is not enough to achieve this goal. To enhance the database performance, sometimes it may be necessary to go the other way around to try out database denormalization. This article will take a deeper look into the denormalization process and find out when and how to use it for better database performance.
When should we try to denormalize?
With a unique objective to increase a web application or website’s speed and performance, denormalization is often just a starting point based on your objective. This means that you should first normalize the DB structure to make it viable. As we have discussed in another article in this series, normalization is putting each piece of data in a table to an appropriate place for easy retrieval. This process will ensure data integrity and relevance, which would further facilitate updating data quickly and effectively.
However, when it comes to the retrieval of data, normalized databases tend to be slower. In a normalized DB, the queries tend to address different tables to find the pieces of data it looks for. Updating data becomes quicker as each piece of data is stored at a unique place, which is easier to be changed. However, as retrieval is slow most of the time, we may have to think of denormalizing the normalized DB for speed with the web application needs.
The majority of modern-day web applications need to retrieve data in the shortest time. A study showed that an average web user is not ready to wait for more than three to five seconds to get loaded. A slower response will end up in a higher bounce rate, which is a loss in business. This is the reason why you may consider denormalizing when needed on a relational database.
As we can guess from its name, denormalization is the process just in reverse to normalization. When you try to normalize a database, you try to organize the data into tables to keep up data integrity and eliminate redundancies. On the other hand, the database’s denormalization means you are putting the same data in various places, which may increase redundancy. If you are confused about your database manipulation initiative, try to contact a good consultant like Remotedba, which offers cost-effective services for remote database administration.
As we have seen, the primary purpose of data denormalization is to speed up data retrieval. Denormalization is not a magic pill to get it done. The developers and administrators need to consider related aspects too to enhance the speed of data retrieval. Let us further explore how denormalization can help you out with your data retrieval goals.
Enhancing the query performance
A normalized DB needs to join many tables to fetch data while running the queries in general cases. However, the more the number of joins is, the slower the query response will be. Being a countermeasure to the same can add more redundancy to the database by copying the values between the parent-child tables and reducing the number of joins needed for a query.
Making the database easier to manage
As we have discussed, normalized databases do not have any calculated values essential for the applications. Calculating the go’s values may require some time, which will further slow down the execution of queries. You can effectively denormalize the database to give the calculated values. Once those are generated and added to tables, the programmers can easily create the reports and queries even without any in-depth knowledge of the API of apps code.
Facilitating and accelerating the reporting process
Often, web applications may have to provide statistical and analytical info in terms of reports. Generating such reports using live data is very time-consuming and may also negatively impact system performance. Denormalizing the database will help you to meet up this challenge effectively. Suppose you have to provide a complete sales summary of a particular user or user group. A normalized database tends to aggregate all involved and calculate the details multiple times. This would be highly time-consuming, and you may not get it handy for the need for an on-the-go presentation or so. To speed it up, you may maintain a year-to-date sales summary by storing the user details.
Demoralizing Your Database
Now you the basics as to when you have to think of demoralizing your database. Now, let us check out when you should consider it. There are various types of denormalization approaches, which you need to adapt based on the situation’s need. The most common techniques of data denormalization are as below.
- Store the derivable data, which you can try if the need is to execute a particular calculation of multiple types during the querying.
- Denormalization through storing the derivable data. This is ideal when you are making an email messaging platform or so.
- By using the pre-joined tables. In this approach, you have to add non-key columns to the table, which does not bear any business values. This way, you can easily dodge the joining tables and thereby speed up the queries. However, you have to ensure that the database’s denormalized columns get updated each time the master column gets alerted.
We may have a detailed discussion of these denormalization modalities in another article. You may thoroughly review the above information if you plan to implement measures to speed up your database and take adequate denormalization measures as specified by an expert.