Data redundancy in a database means storing the same data in multiple places within a database. It can happen intentionally or unintentionally. Redundancy plays an important role in database management.
Types of Data Redundancy
The following are the important types of data redundancy:
1. Unintentional Redundancy
This happens when the same data is saved in multiple places unnecessarily. It is usually a result of poor database design.
How it occurs
Imagine you have a database that stores student information. If the same student’s name and details are added multiple times, it causes unintentional redundancy.
2. Intentional Redundancy
Intentional redundancy is to improve data availability and reliability. This type is carefully planned during database design or system setup.
How it works
For example, in large online systems like banking, the same data is saved on multiple servers to ensure it’s available even if one server fails.
3. Coding Redundancy
Coding redundancy occurs when data is stored or transmitted using more bits than necessary. This type of redundancy is often found in data compression techniques.
How it works
Imagine sending a message like “AAABBBCC.” Instead of repeating the same letters, we can use coding techniques to write it as “3A3B2C.” This reduces the number of bits needed to represent the data.
4. Psychovisual Redundancy
Psychovisual redundancy is a type of data redundancy related to how humans perceive visual information. It refers to parts of an image or video that are not noticeable to the human eye and can be removed without affecting the overall quality.
How it works
In video streaming, small changes in colour or brightness may not be noticed by viewers. Compression techniques remove this unnecessary data to make the file smaller.
5. Geographic Redundancy
Geographic redundancy involves storing duplicate copies of data in different geographic locations. This type of redundancy is used to ensure data availability to protect against a disaster, such as a power outage or natural calamity.
How it works
A cloud storage company like Google Drive or Dropbox stores your data in servers located in different countries. If one server fails, another server can provide your data.
6. Interpixel Redundancy
Interpixel redundancy occurs in digital images where nearby pixels have similar or identical values. This is common in regions of an image with uniform colours or patterns.
How it works
In an image of the sky, many pixels may have the same shade of blue. Instead of storing each pixel separately, compression methods group similar pixels together to save space.
How Does Data Redundancy Work?
Data redundancy occurs when the same data exists in multiple places. This can happen unintentionally due to databases are not designed efficiently or it can be done intentionally to make data more secure or accessible.
For example, Think of a school database. The school might have a table called “Students” where all the information about students is stored, like their names, IDs, and phone numbers. Now, imagine there is another table called “Attendance,” and the same phone numbers are also saved there. This is an example of data redundancy.
Benefits of Data Redundancy
Here are the advantages of data redundancy:
- Improves Data Reliability: If one copy of the data is lost, the other can still be used.
- Increases Data Availability: Redundancy ensures that critical data is always accessible.
- Faster Data Recovery: During a system failure, redundant data helps restore operations quickly.
- Better Performance in Certain Cases: For large systems, having data in multiple places can make it faster to retrieve.
Drawbacks of Data Redundancy
Here are the disadvantages of data redundancy:
- More Storage Usage: Duplicate data takes up extra space on storage devices.
- Risk of Inconsistency: When changes are made to one copy of data but not the other, errors can occur.
- Slower Performance: Searching or updating multiple copies of the same data can take more time.
Redundancy in Storage
Data redundancy is closely linked to how data is stored. It is common in both physical storage devices and cloud storage systems.
Physical Storage
In physical storage, organizations store the same data on multiple hard drives. If one drive stops working, the other drive still has the data.
Example: A company may store employee records on two different servers.
Cloud Storage
In cloud storage systems like Google Drive, data is stored on multiple servers in different locations. If one server fails, the data can still be accessed from another server.
Redundancy in storage systems provides a safety net. It ensures that data is not lost.
Data Redundancy vs. Backup
Many students confuse redundancy with backup. Although they are related not the same thing. The following table shows the difference between data redundancy and backup:
| Feature | Data Redundancy | Backup |
|---|---|---|
| Definition | Data is stored in multiple locations within the same system. | A copy of the data is created and stored separately. |
| Purpose | Ensures real-time availability of data, even during system failures. | Restores data in case of accidental loss, corruption, or disasters. |
| Location | Copies are usually stored within the same system or storage infrastructure. | Backups are typically stored on external devices, cloud systems, or offsite storage. |
| Real-Time Access | Provides immediate access to redundant copies for seamless operation. | Requires a recovery process to access and restore the data. |
| Use Case | Protects data during live operations to avoid downtime. | Protects against data loss due to accidental deletion, malware, or physical damage. |
| Storage Requirements | Consumes more storage space as identical data is duplicated across the system. | Requires less frequent storage usage but needs additional space for storing complete backups. |
| Example | An airline system storing flight data on multiple servers to ensure uninterrupted service. | Recover lost or corrupted data to its original state. |
| Focus | Prevents data unavailability by ensuring system resilience. | Recovers lost or corrupted data to its original state. |
| Dependency on System | Works within the active system to maintain data availability. | Can work independently of the main system for disaster recovery. |
| Data Version | Usually involves storing identical and up-to-date copies. | Can include older versions of data based on the last backup point. |
Redundancy in RAID
RAID stands for Redundant Array of Independent Disks. It is a storage technology that uses redundancy to improve reliability and performance. RAID creates copies of data across different drives. This helps recover data if one drive fails.
Types of RAID and Their Redundancy
Here are the RAID types and their uses of redundancy:
1. RAID 1 (Mirroring)
In this RAID type data is stored as an exact copy on two or more drives. For example, If one drive fails, the data is available on the other drive. The primary benefit of RAID 1 is High reliability.
2. RAID 5 (Striping with Parity)
Data is divided into blocks and stored across multiple drives with a parity check in RAID 5. For example, If one drive fails, the data can be reconstructed from the parity information on the other drives.
3. RAID 6 (Double Parity)
RAID 6 is similar to RAID 5 but with two layers of parity. For example, Even if two drives fail, the system can still recover the data. They provide extra protection for critical data.
