If you deal with data, you'll hear the words “data redundancy” quite often. Simply put, it means storing the same data in more than one place at the same time within a system or database. At surface value, it seems like a no-downside situation. After all, data redundancy is just another type of backup, right? Wrong. While having redundancy in your database has its advantages, if improperly managed, it can lead to various problems.
This article will cover everything that you need to know about data redundancy.
And so, without any further ado, let's get right into it.
What is Data Redundancy?
Data redundancy is when the same piece of data is stored in multiple locations, whether by design or by accident. Below are two examples to help you better understand data redundancy.
First, a bank that stores customer transaction histories on multiple servers across different locations. This means that if one server fails, another can provide the exact transaction records without delay. So, during maintenance or patching, operations are not affected.
Next, a university that maintains student contact information in both the "Student Records" and "Financial Aid" databases. Each time a student changes their address or phone number, staff will need to update both databases separately.
In the first case, redundancy is a good thing, it's like a data backup. It helps with data loss prevention in case something goes wrong. In the second case, having data redundancy is more of a hindrance than a help — causing more problems than it fixes.
So then, now that you know what data redundancy is, let's talk about how it happens.
How Data Redundancy Occurs?
Many things can lead to data redundancy. Here are the top ones:
Intentional Design:
Sometimes, you'll create data redundancy on purpose. You might do this for backup purposes, to improve system performance, or to make data more accessible.
Poor Database Design:
If you're not careful when designing your database, you might accidentally create redundant data. This often happens when you don't properly normalize your database structure. For instance, you might store a customer's address in both the customer table and the order table, leading to unnecessary duplication.
Data Integration Issues:
When you're upgrading or downgrading your systems, you'll often merge data from different sources. During this process, you might end up with redundancies. It's commonplace to see it happen, especially during mergers or when combining departments.
Poor Inter-Team Communication:
Another common sight is when teams inside the company create their own data sets. Often, they won't bother to check whether or not that information exists elsewhere. For instance, the sales team might maintain a customer database that overlaps with marketing.
Data Migration Issues:
As your business grows, you might move data from old systems to new ones. During this process, instead of replacing the old data, you might end up keeping both versions running parallel. It's similar to when you upgrade your phone but keep your old one "just in case".
Those were the five most common causes of data redundancy. With that out of the way, let's take a look at the advantages and disadvantages.
Advantages of Data Redundancy
The main advantages of redundant systems for data are listed below:
- Enhanced Data Backup and Recovery: Data redundancy provides an effective form of backup. By storing multiple copies of data across different locations or systems, you're creating a safety net. If your primary data source fails, you can quickly recover from redundant copies.
- Improved Data Integrity: Redundant data allows for cross-verification, enhancing data integrity. When you have multiple copies of the same information, you can compare them to identify and correct inconsistencies.
- Increased System Availability: You reduce the risk of complete system failure. If one component fails, the redundant systems can seamlessly take over. For example, if you have three computers and only need two, the third can act as a redundant system. So if one computer fails, device #3 kicks in so that operations don't stop. It's the same with data. If there's a dataset that everyone needs to access, you can duplicate it for redundancy and have the same effect.
- Load Balancing: Having data redundancy can actually help improve performance. Say you have a dataset that is accessed quite frequently, and information is called from it often. To not bottleneck performance, and have the double benefit of system availability described in point #3, you can have multiple copies of the database.
- Data Loss Prevention: By maintaining multiple copies of critical data, you create a safeguard against accidental deletions, hardware failures, or malicious attacks. This redundancy ensures that even if data is compromised in one location, intact copies remain available elsewhere. That's why many storage solutions have data redundancy built in.
With the advantages of data redundancy out of the way, the next section will talk about the cons.
Disadvantages of Data Redundancy
Data redundancy is not without its share of downsides. Here are the most common ones you should know about:
- Increased Storage Costs: If you're storing 1 TB of data with two redundancies, you'll actually be paying for 3TB of storage. This problem will only compound at the enterprise level, more so if you're using cloud storage.
- Data Inconsistency: If you decide to make a change in a dataset with redundancy and forget to update the redundant sets, you'll face a whole slew of errors. Imagine changing a customer's phone number in your sales database but not in your support system. Now your support team is calling the wrong number, your delivery notifications are going to the old contact, and your customer is frustrated.
- Slower Data Updates: Having data redundancy means every change requires multiple updates. If you're modifying employee records that exist in five different places, you're taking 5x the time, increasing the chances of making an error.
- Higher Risk of Corruption: If you have redundant systems in place and one copy of the data gets corrupted or infected with malware, it'll copy over to other systems as well.
- Slower Performance: If you've got redundant systems but don't store them in different locations, you'll kill your server performance and speed. And if you do choose to have them in different locations, you'll be raising your maintenance and running costs.
Those were the five main cons of having systems with data redundancy. Now you know what data redundancy is, how it comes about, and its main pros and cons.
Recovering Corrupted Databases
As we mentioned above, data redundancies can lead to corruption and data loss. If this happens, you should take your systems offline immediately and cease all operations on them to avoid overwriting your data.
Stellar's Data Recovery Services were designed for exactly these types of situations.
- Our technicians can help recover data lost from redundant arrays, entire RAID servers, or even from cloud providers in certain cases.
- We can work with all kinds of storage media, including magnetic, flash drive, and solid-state drive.
- If you prefer a physical consultation, we have branches in 14 major Indian cities, ensuring a data recovery center near you.
- With upto 100% success rate, Stellar Data Recovery services give you the best chance of recovering your data.
Simply visit the website and fill out a consultation form and one of our friendly experts will get back to you.
With that, we've reached the end of this article on data redundancy. We hope you found it useful.
FAQs
Generally, experts recommend a 3-2-1 rule for redundant systems. You make three copies of important data and store them in two locations, and one location must be off-site.
To begin with, it can cause malware to spread amongst otherwise isolated systems. It can result in data mismatches which can cause confusion among internal teams. Among other things, it can slow down performance, make websites unusable, and increase storage costs for a business.
In some industries that are regulated, like Finance or Healthcare, you legally need to have data redundancies. However, the redundant sets must match the same level of security as the master set for audit purposes. This could increase data management costs significantly.
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