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Full vs. Incremental vs. Differential Backup

Redstor posted in Cloud backup | 7 Sep 2023

One crucial aspect of data protection is choosing the right backup strategy. Full, incremental, and differential backups are three common approaches, each with advantages and disadvantages.

This article will explore these backup methods to help you determine which one best suits your needs.

Full Backup

As the name suggests, a full backup involves copying all the data from a source to a backup destination. This is a comprehensive and straightforward method of data backup.

Advantages of Full Backup:

  1. Full backups guarantee the backup of every piece of data on the source system, ensuring complete data recovery. If there is data loss or system failure, you can restore your entire system to its previous state.
  2. Full backups are independent of previous backup sessions. Every complete backup generates an independent replica of your data, simplifying the process of finding and recovering particular file versions.
  3. This method is easy to set up and manage. You only need to initiate a full backup at regular intervals (e.g., daily, weekly, or monthly).

Disadvantages of Full Backup:

  1. A full backup can be resource-intensive, requiring storage space, time, and network bandwidth. This method can be particularly demanding if you have a large amount of data.
  2. Full backups can be time-consuming as they require copying all data, which may result in downtime during the process.
  3. You must perform more frequent backups to keep data up-to-date, which demands more resources.

Incremental Backup

Incremental backup is a better way to back up data. Incremental backup is a more efficient method of data backup.

It only saves the data that has changed since the last backup. This includes both full backups and previous incremental backups. This method reduces the amount of data transferred and stored, making it an attractive choice for organizations with limited resources.

Advantages of Incremental Backup:

  1. Incremental backups are efficient both in time and storage. The backup system only backs up new or modified data, significantly reducing the backup window and resource usage.
  2. Incremental backups transfer only changes, resulting in less network bandwidth usage. This is advantageous for remote backups or when dealing with limited internet connectivity.
  3. When restoring data, you only need to combine the most recent full backup with the latest incremental backup. This process is quicker than restoring from a full backup.

Disadvantages of Incremental Backup:

  1. Incremental backups are dependent on previous backups. To restore data, you need the most recent full backup and all the subsequent incremental backups in the correct order. If any backup in the chain is missing or corrupted, it can affect data recovery.
  2. Incremental backups can be harder to handle than full backups, especially with many backup files and their dependencies.
  3. Incremental backups depend on previous backups. Problems with the initial full backup or subsequent incremental backups can cause data loss.

Differential Backup

Differential backup is a middle-ground approach between full and incremental backups. It captures all data that has changed since the last full backup. This means the differential backup grows larger with each backup session but smaller than a full backup.

Advantages of Differential Backup:

  1. You only need the most recent full backup and the latest differential backup to recover data. This process is quicker than restoring from a full backup and all incremental backups.
  2. This process is quicker than restoring from a full backup and all incremental backups.
  3. Differential backups are simpler to handle than incremental backups. They only need the latest full backup, making it easier to manage multiple backup chains.
  4. Differential backups use fewer resources than full backups, even though they are bigger than incremental backups.

Disadvantages of Differential Backup:

  1. The backup size grows over time, especially when performing frequent differential backups. This can increase storage requirements.
  2. Differential backups are less efficient than incremental backups because they get bigger with each backup session.
  3. Like incremental backups, differential backups are dependent on the most recent full backup. Any part of the backup chain that is missing or damaged can affect data recovery.

Choosing the Right Backup Strategy

Selecting the appropriate backup strategy depends on your specific needs, resources, and tolerance for downtime. Here are some considerations to help you make an informed choice:

1. Data Size and Resources

Full backups might be suitable if you have a large amount of data and ample storage resources. However, if resources are limited, incremental or differential backups can be more efficient in storage space and time.

2. Recovery Time Objective (RTO)

Consider your organization’s RTO – the maximum acceptable downtime. Full backups take longer to restore, so incremental or differential backups may be preferable if you require rapid recovery.

3. Frequency of Backups

How often do you need to back up your data? If you require frequent backups, incremental backups can help minimize resource usage. For less frequent backups, differential backups strike a balance between efficiency and speed.

4. Complexity of Management

Evaluate your backup management capabilities. Full backups are the simplest to manage, while incremental backups require meticulous attention to ensure the integrity of the backup chain.

5. Data Dependency

Consider the importance of having independent backups. If maintaining separate backup chains is critical for your data recovery strategy, full or differential backups may be more suitable.

6. Storage Costs

Factor in the cost of storage. Full backups require the most storage space, while incremental backups are more space-efficient.


Full, incremental, and differential backups have merits and drawbacks, making them suitable for different scenarios. The choice depends on factors like data size, resources, recovery time objectives, backup frequency, management complexity, data dependency, and storage costs.