What is Database Replication?[+Types, Benefits, Steps and Challenges]

How horrifying it would be to lose important data at the business level because you have suffered a system or server crash. Data replication is crucial for organizations of all sizes to remain competitive in today’s market. However, managing data replication can be challenging as it depends on factors such as the data volume, the database management system (DBMS) type, and the frequency of data updates.

In this blog, you will learn about database replication, its, types, how it is done, and its importance. Moreover, the blog will explain its advantages and challenges and list the popular tools that can simplify the replication process for you. Read along to learn more about this essential process!

What is Database Replication?

Data replication can simply be the task of making copies of the data stored in Databases on one server and regularly transferring those copies to other Databases located on different servers. The idea is to store the same data in multiple locations so that everyone connected to it distributes the system and has access to the same shared data.

In this way, all users share the same level of information. The result is a distributed database system in which users can quickly access data relevant to their tasks without interfering with the work of others. 

The key aspect of this process is that this copying of data must occur very frequently so that any new changes in one database could be reflected throughout the distributed system. Organizations use different types of data replication strategies, such as full replication, incremental replication, and log-based replication, depending on their needs, resources, and the extent of data they wish to copy.

Key Components:

• Change Data Capture (CDC): A mechanism for detecting and capturing changes (inserts, updates, and deletes) in the source database.
• Source Database: The original database where the data resides.
• Target Database: The database that receives the replicated data.
• Replication Agent: A software or process that handles data extraction, transformation, and loading (ETL) between the source and target.

How does Database Replication work?

Database Replication is the process of copying the same data from one Database to different locations. For example – data can be copied between 2 on-premises, between hosts in different locations, to multiple storage devices on the same host. This can even include Cloud-based hosts. However, many platforms can be used for Data Replication. It also involves different techniques like transferring data in bulk or batches and replication to be scheduled at intervals or should happen in real-time. All this is based on the business requirements and available resources.

Why is Database Replication Important?

• Data Reliability and Availability: Because of Data Replication, the availability of data becomes easy. As mentioned in the introduction, it plays a vital role when a server crashes under extraordinary conditions. So it provides the backup of the Database and hence saves the day as data is available in other locations.
• Disaster Recovery: In the case of Server loss, Data Replication provides disaster management as it gives a copy of the latest data changes. 
• Server Performance: When data is being processed and run on multiple Servers instead of one, it makes data access very quick. Moreover, when all data read operations directs to a replica, admins can reduce processing cycles on the primary Server for more resource-exhaustive write operations.
• Better Network Performance: Keeping copies of the same data in various locations can reduce data access latency as you can retrieve the required data from the location where the transaction executes. For example, users in Asian or European countries may face latency issues when accessing data from Australian data centers. However, placing a Replica of this data somewhere close to the user can enhance access times while balancing the load on the network.
• Enhanced Test System Performance: Replication simplifies the distribution and synchronization of data for test systems that mandate quick accessibility for faster decision-making.

Database Replication vs Data Replication vs Backup

Aspect	Data Replication	Database Replication	Backup
Definition	Copies and syncs data across systems.	Copies and syncs entire databases.	Creates restorable data snapshots.
Purpose	Ensures availability and consistency.	Enables database availability and scalability.	Protects against data loss.
Real-Time	Often real-time or near real-time.	Typically real-time, depending on setup.	Periodic (e.g., daily, weekly).
Scope	Any type of data (files, logs, etc.).	Limited to database objects and tables.	Entire datasets or specific directories.
Use Case	System integration, real-time analytics.	High availability, failover, load balancing.	Disaster recovery and archival.
Consistency	Maintains data consistency across systems.	Ensures consistent database copies.	Provides a point-in-time copy.
Accessibility	Directly accessible for operations.	Accessible for queries or updates.	Requires restoration before use.
Recovery	Not recovery-focused.	Supports failover and disaster recovery.	Recovery-centric.
Tools	Apache Kafka, AWS S3 Replication.	MySQL, PostgreSQL, AWS DMS.	AWS Backup, Veeam, Google Cloud Backup.

What are the Types of Database Replication?

There are generally the following three types of data replication possible from Databases:

• Full Replication
• Key-Based Incremental
• Log-based Replication

1) Full Replication

As the name suggests, Full data replication involves copying of everything, including existing, updated, and new data from the source to the target. This method is helpful if the records are hard deleted from the source regularly or if the source has no suitable column for Key Based Incremental or Log Based. 

Advantages:

• You can ensure that all inserts, updates, and deletes are recorded since this duplicates the complete table, so you will always have the proper data set after each sync.

Drawbacks

• It requires more processing power.
• Generates larger network loads than just copying only changed data.
• Cost increases as the number of rows getting copied increases, irrespective of the tool you are using.  
• This kind of DB replication uses a lot of resources and is the least effective as it duplicates all of the data in a table, regardless of whether it has changed or not. Depending on the amount and quantity of the data in the tables, this may potentially result in a burst strain on the source. 

2) Key-Based Incremental

Key-Based Incremental Data Replication is a method in which the data sources, like PostgreSQL, Oracle, Kafka, Snowflake, and SalesForce, etc. identify new and updated data using the column called the Replication Key. A key can be a timestamp, integer, or datestamp column in the source table. 

The following SQL query is related to the above-mentioned method:

SELECT replication_key_column,
      column_of_choice_1,
      column_of_choice_2,
      [...]
FROM schema.table
WHERE replication_key_column >= 'last_saved_maximum_value'

Key-Based Replication is a popular method, and it becomes very active, especially when Log-Based Replication is not working. 

Note: Key-based incremental Replication does not detect deletes in the source.   

Advantages:

• Because it simply copies updated and inserted rows, key-based incremental replication uses less resources than other forms of replication.

Disadvantages:

• Hard-deleted data from a database cannot be restored to the location of your choice unless a significant amount of time and effort is dedicated to procedures that can detect deletes.

3) Log-based Replication

Log-based Replication is a method in which modifications are recorded to make necessary changes. For example, updates, inserts, and deletes using the Database’s binary log files. 

The log-based Replication method is available only for MySQL, PostgreSQL, and MongoDB backend Databases that support Log Replication.

Advantages:

• This kind of replication is the most effective because it reads directly from the binary log files and doesn’t compete with other database queries.

Disadvantages:

• Only certain databases provide log-based replication, and if your database is hosted by a third party, you might not have access to its logs.
• Additionally, if you develop log-based replication yourself, it may be quite complex, time-consuming, and prone to bugs.

What are the Steps to perform Database Replication?

• Step 1: The first step is to narrow down the data source and the target system.
• Step 2: Now, choose tables and columns that need to be copied from the source.
• Step 3: You need to identify how frequently updates are required to be made.
• Step 4: Now, select a data replication technique (full, partial, or log-based).
• Step 5: Next, write custom code or use data replication software to perform the process.
• Step 6: Lastly, closely monitor how the data extracts, filters, transforms and loads to ensure quality.

What are the Database Replication Challenges?

Although Data Replication adds much value to your work and your company, it still comes along with the following challenges:

• Higher Costs: When you have to maintain multiple copies of the same data over various locations, it results in higher costs as it requires more hardware and processing power to perform basic functionalities on the data. 
• Time Constraints: You need time to perform data replications and experts to perform the job and make sure that Data Replication is appropriately done. 
• Bandwidth: To preserve consistency across Data Replicas, you need better bandwidth as it can result in increased traffic. 
• Inconsistent Data: It could be a tricky point when the environment is distributed because copying of data from different locations at different intervals can lead to some data not syncing with the rest of the data. So, data admins must make sure that data is updated. 
• Data Replication Tools Availability: There are multiple data replication tools available in the market to make your life easy.

Things to Avoid in Database Replication

Database replication is a complex process that involves many steps, and we have to be cautious when it comes to managing the data. A few key points you should avoid are listed below:

1. Inconsistent Data

Data replication mostly takes a complex path because it involves making concurrent updates in the database. Continuously replicating data from multiple data sources can cause problems, and many times, one or the other replication process goes out of sync even for hours. Database administrators are responsible for ensuring consistent data replication and that all the databases remain in sync.

2. More Data Means More Storage

Data replication is copying the data to single or multiple databases from the primary database. As the storage of the primary database increase, so as the need for more storage in replicas. So, it is always a good practice to plan and factor in the cost when it comes to planning a data replication project.

3. More Data Movement Requires More Resources

Writing a huge volume of data in distributed databases requires more processing power and slows down the network. To efficiently continue the data replication, one should optimize the data and database to manage the increased load.

4. Lost Data

If database objects in the source database are set improperly, or if the primary key you use to confirm data integrity in the replica is wrong, some of your data can be lost.

5. Multiple Servers

There are inherent maintenance and energy costs involved with running several servers. These expenses must be covered by the organization or by a different party. The company bears the risk of vendor lock-in or uncontrollable service problems if they are handled by a third party.

A Simple Database Replication Example

PostgreSQL replication allows data from one database server to be copied to another. The primary server is the main database where changes are made, while the replica server receives those changes and keeps an up-to-date copy.

How Does It Work?

1. Data Flow:
   All write operations happen on the primary server. After a change is made, it’s sent to the replica server, ensuring both databases stay synchronized.
2. Replication Methods:
   PostgreSQL offers different ways to replicate data:
   • Incremental Backups: Periodic updates based on recent changes.
   • Volume-Level Replication: Entire database volumes are copied.
   • Streaming Replication: Continuous, real-time data updates using Write-Ahead Logging (WAL).

What Is Streaming Replication?

Streaming replication, also called WAL replication, is a standard process in PostgreSQL. Here’s how it works:

• Every database change is recorded in a Write-Ahead Log (WAL).
• These logs are transferred from the primary server to the replica server in chronological order.
• This ensures accurate and consistent replication of data.

In a typical setup:

1. The primary server hosts the main database.
2. The secondary server acts as a backup, applying changes from the primary server to create an exact copy.

Once PostgreSQL is installed on both servers, you can configure WAL to handle the data transfer automatically. This setup ensures data reliability, consistency, and real-time synchronization between servers.

What are the Best Database Replication Tools?

1. Built-In Database Features:
   • MySQL Replication
   • PostgreSQL Logical Replication
   • SQL Server Replication
2. Cloud-Based Solutions:
   • Google Cloud Datastream
   • AWS Database Migration Service (DMS)
   • Azure Data Sync
3. Third-Party Tools:
   • Hevo Data
   • Qlik
   • Fivetran

To know more about database replication tools, check out our blog. 

Conclusion

In this blog, you have learned about database replication, its types, how to achieve it, and its importance. Moreover, it explained how it differs data replication and listed the most popular tools for database replication. However, if you are looking for an easy solution, then try Hevo.

Hevo is a No-code Data Pipeline. It supports pre-built integrations from 150+ data sources, including MySQL, Oracle, PostgreSQL, etc., at a reasonable price. Hevo provides a fully automated solution for data migration.

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