Nothing is more important than data in today’s world. 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 a tricky thing 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 down the popular tools that can simplify the Replication process for you. Read along to learn more about this essential process!
Table of Contents
What is Database Replication?
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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 like Full Replication, Incremental Replication, and Log-based Replication depending on their needs, resources, and the extent of data they wish to copy.
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How does Data Replication work?
Data 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 Database Replication is Important?
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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 provides 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.
What are the Advantages of Database Replication?
The process of Data Replication can provide the following major advantages to your business:
- Ensure a consistent copy of the data across all nodes in the Database. As a result of this, data is more easily available.
- Data reliability is enhanced by Data Replication. Moreover, it allows multiple users and provides high performance.
- To eliminate any data redundancy, Master Databases and slave Databases are updated with stale or incomplete data.
- Because copies are made, there is a possibility that the data will be present where the transaction is being performed. This reduces data movement. It increases the speed of query execution which saves you and your company a lot of time.
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:
1) Full Replication
Full Database 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.
Few drawbacks that this method offers are listed below:
- 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.
2) Key-Based Incremental
Key-Based Incremental Data Replication
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.
Please note that Key-based incremental Replication does not detect deletes in the source.
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.
Log-based Replication method is available only for MySQL, PostgreSQL, and MongoDB backend Databases that support Log Replication.
Log-based Data Replication
What are the Steps to perform Database Replication?
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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.
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:
1) Hevo Data
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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.
2) Rubrik
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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
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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
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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 involving Heterogeneous Replication among Databases. If you want to expand from on-base replication to the cloud, this tool will be perfect for you.
Database Replication vs Mirroring
Mirroring involves, creating a backup Database Server as a safety measure for the Primary Database Server. This is done to safeguard the data availability of your company.
So, in a situation where the Primary Database Server is down, the Mirrored Database Server will act as the main source of data. it is important to note that, out of the Primary Database Server and the Mirrored Database Server, only one will be active at a time. The Database Mirroring process is shown in the below image. Also, check out Replicate Database.
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Database Replication, on the other hand, means storing multiple copies of a Database across multiple geographic locations. The classic example of Replication is File Servers that are copied and stored across all continents, enabling users to download files from the closest location to avoid network delays and any slow responses. The Database Replication process is shown in the below image.
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The following points will further explain the difference between Database Replication and Database Mirroring:
- Database Replication is implemented on Database Objects while Mirroring involves the whole Database.
- When it comes to Distributed Database Systems, Mirroring can’t be implemented. Data Replication, however, thrives in such situations.
- The main objective of Mirroring is to create a backup while Data Replications aim at increasing the distribution efficiency of data.
- Data Replication is relatively cheaper as compared to Mirroring.
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 Mirroring and also listed the most popular tools for Data Replication. However, if you are looking for an easy solution, then try Hevo.
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Hevo is a No-code Data Pipeline. It supports pre-built integrations from 100+ data sources, including MySQL, Oracle, PostgreSQL, etc. at a reasonable price. Hevo provides a fully automated solution for data migration.
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Share your experience of Database Replication in the comment section below.