Database Replication: 6 Comprehensive Aspects

How horrifying it would be to lose important data at the business level because you have suffered a system or server crash. The importance of Data Replication is an adamant thing that every small, medium, or large organization has to adapt to survive in the competition. Data replication can be tricky to manage as it depends upon the size of the data, the type of DBMS, and how frequently data is being updated.

In this blog, you will learn about Database Replication, types of Database Replication, how it is done, and its importance. Moreover, the blog will explain the advantages and challenges of database replication 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 be simply described as 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 like Full Replication, Incremental Replication, and Log-based Replication depending on their needs, resources, and the extent of data they wish to copy.

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. Though 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?

Database Replication is important because of the following reasons:

• 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.

You have learnt how does database replication works. Now, let’s look into the benefits of the replication.

Database Replication vs Data Replication

Feature	Data Replication	Database Replication
Definition	The process of copying data from one location to another.	The process of copying and maintaining database data across multiple servers.
Scope	Specifically, it focuses on the data within a database management system (DBMS).	Specifically focuses on the data within a database management system (DBMS).
Purpose	Ensures data availability, backup, and disaster recovery.	Provides high availability, load balancing, and data consistency across databases.
Use Cases	Useful for data sharing, data warehousing, and backup solutions.	Commonly used for high-availability setups, distributed databases, and scaling applications.

What are the Types of Database Replication?

When it comes to Database Replication, there are generally the following 3 types of Data Replication possible from Databases:

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

1) Full Replication

As the name suggests, Full Database 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 not a suitable column for Key Based Incremental or Log Based. 

Advantages:

• You can make sure 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 that exists in the source table. 

When you are Replicating the table using Key-based Incremental Replication, the following things will happen:

• During a replication job, PipelineWise stores the maximum value of the table’s replication key column. 
• During the next replication job, the above-stated data sources will compare saved values from the previous job to the Replication key column values in the source. 
• Any rows in the table with a Replication Key greater than or equal to the stored value are replicated. 
• PipelineWise stores the new maximum value from the table’s Replication key column.

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 database 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:

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

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?

Here are a few steps that are required 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 done properly. 
• 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 in Database Replication are listed below:

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 Database 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.

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.

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.

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.

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

Data replication from one PostgreSQL database server to another is known as PostgreSQL replication. The primary server is the name of the original database, and the replica server is the name of the server that receives the replicated data.

Every write in PostgreSQL goes through the main node. After modifications are performed there, they are announced to the secondary nodes. We have the option of using incremental backups, volume-level replication, or PostgreSQL streaming replication.

WAL replication is another name for PostgreSQL streaming replication. The standard procedure known as WAL is employed to guarantee that all database modifications are accurately recorded in the chronological sequence in which they occur.

After PostgreSQL is installed on all servers, WAL may be configured to enable the migration of WAL files from the primary database to the target database. In the example, a primary-secondary setup is employed. The primary database will be hosted on the primary server in this arrangement. The secondary server serves as the backup instance when modifications are made to the primary database, applying those changes to itself by creating an exact replica.

What are the Best Database Replication Tools?

There are numerous tools available in the market that can efficiently carry out your Data Replication work. The following tools are the most popular in the current business markets:

• Hevo Data
• Rubrik 
• Carbonite
• SharePlex

1) Hevo Data

Hevo Data, a No-code Data Pipeline, helps to transfer data from 150+ sources to your desired Data Warehouse/ Destination and visualize it in a BI tool. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

Key features of Hevo

• Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer.
• Schema Management: Hevo can automatically detect the schema of the incoming data and maps it to the destination schema.
• Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.

2) Rubrik

Rubrik is a Cloud-based Data Management and backup tool that provides instant backup, archive, restore, analysis, and copy management of data. It offers simplified backup and integration with modern data center technologies. With an easy-to-use interface, you can easily host and authorize any user group.

3) Carbonite

Carbonite is a popular database replication software. It provides both Data replication and Disaster Recovery options in a combined pack. It is one of the few tools that can handle the duplication of physical as well as virtual environments. Carbonite works best in a scenario where continuous Data Replication is required without any time constraints.

4) SharePlex

SharePlex is one of the few tools that implement real-time Data Replication. The tool supports many types of Databases and is highly customizable. Thanks to its message queuing mechanism, it provides fast data transfer and high scalability. SharePlex is best for the process of heterogeneous replication among databases. If you want to expand from on-base replication to the cloud, this tool will be perfect for you.

Conclusion

In this blog, you have learned about Database Replication, types of Database replication, how to achieve it, and its importance. Moreover, it explained the difference between data replication and database 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.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite firsthand. Share your experience with database replication in the comment section below.

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