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The Essential Guide to Database Backup: Tips & Strategies

Database backup and recovery are fundamental aspects of data management, ensuring the preservation and restoration of vital information within a database system. To implement an efficient database backup strategy, we need to learn the methods, understand the pros and cons, and then learn how to avoid pitfalls.
Published on
February 19, 2024
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Adam Furmanek
Dev Rel
Metis Team
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Database backup and recovery are fundamental aspects of data management, ensuring the preservation and restoration of vital information within a database system. A database backup involves creating copies of the data stored in a database at a specific point in time, safeguarding against data loss due to accidental deletion, corruption, or system failures. On the other hand, recovery refers to the process of restoring the database to a consistent state after a failure or data loss event. This involves utilizing the backup copies to recreate the database and its contents to ensure business continuity and data integrity.

To implement an efficient database backup strategy, we need to learn the methods, understand the pros and cons, and then learn how to avoid pitfalls. Let’s begin with an overview of different backup methods that we can apply in our business to make it grow.

Understanding Different Backup Methods

There are many ways to create a backup. Full backup, incremental backup, and differential backup are three common methods used in data backup strategies.

A full backup involves making a complete copy of all data within a database or system at a specific point in time. While it offers comprehensive data protection, it can be resource-intensive and time-consuming.

In contrast, incremental backup captures only the changes made since the last backup, significantly reducing storage requirements and backup duration. However, restoring from incremental backups may take longer, as it requires applying each incremental backup in succession until reaching the desired recovery point.

Meanwhile, a differential backup captures all changes made since the last full backup, offering a balance between storage efficiency and restoration speed compared to incremental backups. Differential backups require less time to restore than incremental backups since they only need the last full backup and the latest differential backup.

Organizations often utilize a combination of these backup methods to optimize their data protection strategies based on their specific requirements for recovery time objectives (RTOs) and recovery point objectives (RPOs). It’s important to select the method that lets us restore the database from backup as fast as possible and won’t incur too much downtime. At the same time, we should always strive for automated database backups that don’t overload our systems.

Recommended reading: How to Prevent Database Problems from Hitting Production?

Why is Database Backup Crucial?

We rarely think about things that may go wrong when running our business. We focus on adding more features but we don’t focus on keeping our business in shape. We don’t prepare for critical outages that may take our services down in a split second and for a very long time. 

Database backup is crucial for several reasons. It safeguards against accidental or malicious data loss, whether due to human error, software bugs, or cyberattacks such as ransomware. Without backups, valuable information could be irretrievably lost. This can be also caused by vendor lock-in. If we use things specific to some particular hosting provider, then we won’t be able to easily migrate to another hosting platform. If the current provider suspends our account for whatever reason (be it legal or cybersecurity reasons), we are effectively down with no way to come back up.

Another reason is business continuity. In the event of hardware failures, software crashes, or natural disasters, database backups enable organizations to quickly recover their data and resume operations, minimizing downtime and mitigating financial losses. Backup copies serve as a crucial component of database disaster recovery strategies, allowing organizations to rebuild their databases and restore normal operations following catastrophic events like fires, floods, or earthquakes.

Recommended reading: What Is Database Monitoring & Why You Need It

We may be legally obliged to take backups. Many industries have regulatory obligations regarding data retention and protection. Database backups help businesses fulfill these requirements by providing a means to restore data if needed for audits or legal purposes.

Furthermore, database backups give us safety. Database backups can be used for testing new software releases, patches, or updates without risking the integrity of the production environment. They provide a safe sandbox for developers to experiment with different configurations or code changes.

Last but not least, backups can also be useful for historical analysis, enabling organizations to analyze trends, track changes, and make informed decisions based on past data. While this should be done with dedicated reporting systems (or data lakes), we can use backups to analyze historical data as a first step.

Implementing a Backup Strategy

Now that we understand why backups are crucial, let’s see how to implement a database backup strategy. A couple of things that we need to consider:

  • Regular backups
  • Storage security
  • Testing and monitoring

Effective backup strategies are crucial for ensuring the resilience and integrity of data within an organization. Regular backups form the cornerstone of such strategies, involving scheduled and consistent copies of data to mitigate the risk of loss due to unforeseen events such as system failures, human error, or cyberattacks. Whenever we build a database backup solution, we need to measure the time between taking backups. We need to understand how much data we will lose in case of a failure.

Equally important is the secure storage of these backups, which should be maintained in offsite locations or encrypted cloud environments to safeguard against physical disasters and unauthorized access. We should especially focus on accidental access to the backups as this often leads to destroying or breaking the data.

Furthermore, testing and monitoring backup procedures are essential components to validate the reliability and effectiveness of the backup system. Regular testing ensures that data can be successfully restored within acceptable timeframes, while continuous monitoring helps identify any issues or anomalies that may compromise the integrity of backups.

By implementing comprehensive backup strategies encompassing regular backups, secure storage, and rigorous testing and monitoring, organizations can enhance their resilience to data loss and ensure business continuity in the face of adversity.

Recommended reading: 8 Proven Strategies to Improve Database Performance 

Recovering Data: What You Need to Know

In the realm of database management, various recovery scenarios necessitate prompt and effective responses to maintain data integrity and operational continuity. Let’s see some of these scenarios to understand what may happen.

A crash recovery scenario occurs when the database system unexpectedly halts due to software or hardware failures, requiring the database to be restored to a consistent state using transaction logs and checkpoints. Think about power loss, system reset, kernel panic, driver failure, or wire malfunction. This can happen also due to system restarts for updates or unplugging drives too early. When this happens, we may need to roll back changes that were partially applied and left the system in an inconsistent state.

Another example is data corruption. It may result from software bugs, hardware malfunctions, or malicious attacks, leading to inconsistencies or errors within the database. In such cases, recovery procedures involve identifying and repairing corrupted data using backups or specialized recovery tools to ensure data accuracy and reliability. Think about broken files, bad sectors, or missing pieces of data. We can typically identify these issues by using checksums. However, even correct checksums do not guarantee that the data is correct.

Yet another example is system failure, which encompasses broader infrastructure issues such as power outages or network disruptions, which can disrupt database operations and compromise data availability. Recovery strategies typically involve restoring the database from backups and implementing failover mechanisms to switch to redundant systems, minimizing downtime and ensuring seamless operations.

Recommended reading: Common Challenges in Schema Migration & How To Overcome Them

Once we identify the issue and understand what happened, we can begin the data recovery. This involves a systematic approach to restore lost or corrupted data while minimizing downtime and ensuring data integrity. Let’s see the steps for effective data recovery.

First, we need to begin by assessing the extent of the data loss or corruption. Identify the affected systems, files, and databases, and analyze the root causes of the issue.

Next, we need to determine the available resources for data recovery, including backups, redundant systems, and specialized recovery tools. Assess the quality and reliability of backups to ensure they contain up-to-date and consistent data. Grab your tools and see if they can help with the issue.

Then, prioritize the recovery tasks based on the criticality of the data and the impact of the loss on business operations. Focus on restoring essential data and systems first to minimize disruption and prioritize high-value assets.You want to get back to speed as soon as possible. However, some parts of the system must be restored immediately, while others can wait for a few hours.

[.tip-box]Use file system snapshots for quick data recovery. They're instant, minimize data loss, and allow granular restoration, making them ideal for fast database rollback without the delays of traditional backups.[.tip-box]

After data recovery efforts, verify the integrity and consistency of the restored data. Perform validation checks and integrity tests to ensure that the recovered data is accurate and free from errors or inconsistencies. There is always a risk of data loss (since some data wasn’t captured in the last backup) or incorrect entries that you’ll need to handle manually.

Last but not least, do your post-mortem analysis, understand what went wrong, and make sure that it doesn’t happen again. 

Choosing the Right Database Backup Solution

There are many things we need to consider when choosing the right database backup solution. We need to consider many factors including the size of the data, the frequency of the backup process, and the type of data. We need to think about the provider we use and if we can use cloud-based backup solutions. Let’s see the factors that we should be interested in.

The size of the database and associated data is the most important factor in determining the scalability requirements of the backup solution. Larger databases may require backup solutions capable of efficiently handling large volumes of data without sacrificing performance or requiring excessive storage resources. We can take small databases offline for backup purposes but we can’t do that for bigger ones.

The frequency at which backups need to be performed based on business requirements and data volatility is another important aspect. For mission-critical systems with frequently changing data, more frequent backups (such as hourly or daily) may be necessary to minimize data loss and meet recovery objectives. Depending on the nature of your system, you may be able to take backups easily during the night or after working hours. However, taking backups each night increases the risk of the data being lost.

There are many types of data that we want to back up, including structured, unstructured, and semi-structured data, as well as multimedia files, documents, and system configurations. Choose a backup solution that can accommodate diverse data types and formats while ensuring data integrity and consistency during backup and recovery processes.

Recommended reading: How to Choose a Database for Your Next Project

Finally, select appropriate backup methods based on the type of data and recovery objectives. For large databases with frequent changes, a combination of full, incremental, and differential backups may be needed to optimize backup efficiency and minimize storage requirements while meeting recovery time objectives.

When it comes to money, look for backup solutions that offer data compression and deduplication capabilities to optimize storage utilization and reduce backup storage requirements, especially for large datasets with redundant or repetitive data. You need to keep your backup for a long time and it may become very expensive. Don’t forget to define retention policies for storing backup copies based on regulatory requirements, compliance standards, and business needs. Determine the retention period for backup data, including the duration and frequency of backups needed for data recovery and historical analysis.

Let’s see some examples of backup solutions tailored to different types of data.

Relational Databases:

  • PostgreSQL uses pg_dump
  • Microsoft SQL Server offers built-in backup and restore functionality
  • Oracle has its RMAN (Recovery Manager)
  • MySQL and MariaDB have mysqldump and third-party tools like Percona XtraBackup

Semi-Structured and NoSQL Data:

  • MongoDB offers mongodump
  • Cassandra supports snapshot-based backups
  • Amazon DynamoDB can be backed up with AWS Backup

File Systems, Multimedia, and Large Data Sets:

  • Amazon S3 Glacier provides long-term storage solutions for large data sets and multimedia files, offering low-cost archival storage with configurable retrieval options.
  • Google Cloud Storage offers Nearline storage class for large data sets and multimedia files, providing low-latency access to data with cost-effective storage pricing.
  • IBM Spectrum Protect offers backup and recovery solutions for large-scale data sets, including multimedia files and big data workloads, with features like incremental backups and data deduplication.

There are many more solutions that you can adapt to your needs.

Common Pitfalls in Database Backup and Recovery

Let’s now see some typical pitfalls in database backup and recovery.

The first problem is not running the backup regularly. Overlooking regular backups poses a significant risk to data integrity and business continuity. Without regular backups, organizations are vulnerable to data loss due to unforeseen events such as hardware failures, software glitches, or cyberattacks. Neglecting to establish and maintain a consistent backup schedule can result in irreversible damage, impacting operations, customer trust, and compliance obligations. 

Next, ignoring backup testing can have serious consequences for organizations, leaving them vulnerable to undetected failures and data corruption. Testing backups is essential to ensure their integrity, completeness, and reliability in real-world recovery scenarios. If we don’t test our backups, then they may fail us right when we need them. At least, test your backups once. Never configure a backup without checking if it did what you expected.

Next, we tend to underestimate the data recovery time which can have significant ramifications for organizations, leading to prolonged downtime, missed service level agreements (SLAs), and financial losses. Restoring the backup may take hours. By accurately estimating data recovery time and implementing proactive measures to expedite recovery efforts, organizations can minimize downtime, uphold service commitments, and safeguard their resilience in the face of adversity.


Database backup and recovery are fundamental aspects of data management. You need to be prepared for the issues and be able to restore the data in a short time. There are many factors that you should include and many different strategies that you can take.

Whatever you do, make sure that you test your backups. Be proactive, think about things that may fail and get prepared for them. Examine what solutions you can use and whether your provider can help you with automating the tasks.

Importantly, you need to see when things go wrong. Have good observability solutions in place that can identify issues as soon as possible.


How often should you back up your database?

Your backup processes should be fast, shouldn’t affect the live system, and shouldn’t incur too high costs. Take backups as often as possible.

What is the best method for database backup?

Many solutions depend on the type of data. For SQL databases, each server supports dedicated solutions. For cloud services, we can typically use a dedicated service from the cloud provider. Same for unstructured data, we have solutions that can deal with file systems, NoSQL databases, or other applications.

How to recover a database from a corrupted backup?

Assess what happened and how big the data loss is. Decide whether you can restore the data in place or if you need to replace the existing solution from the backup. Analyze what data may have been lost. Finally, verify that the data is consistent after the recovery.

What are the differences between incremental and differential backups?

The incremental backup captures only the changes made since the last backup, while the differential backup captures all changes made since the last full backup.

Can cloud services be used effectively for database backups?

Many cloud services provide dedicated database backup services. They can automate the process and make it configurable with no code. Cloud database backup should be the first approach to consider when building a backup solution.

What are the risks of not having a disaster recovery plan for databases?

You risk going out of business. When a disaster happens, your systems are offline and can’t serve the purpose. You need to make sure that you can get back online promptly.

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