6 Key Data Replication Best Practices You Must Know

Today, data is both the enabler and the point of differentiation for your organization – if you can use it well. Organizations adopt data replication strategies to ensure that everybody has access to updated data whenever and wherever needed. However, data replication is a complex process with several possible pitfalls. This article covers some crucial data replication best practices so that you can take on the task with confidence.

Table of Contents

• What is Data Replication?
• Pitfalls to Avoid during Data Replication
• Best Practices to Follow during Data Replication
• Final Thoughts

What is Data Replication?

Data replication is the process of copying and storing data across many locations. Data engineers use data replication techniques to make the organization’s data available across locations and storage devices to all who need it. 

The primary benefits of data replication are:

• It reduces latency and improves data availability for users in different locations.
• It helps create backups for disaster recovery.
• It enables real-time insights and better decision-making based on unified, updated data.
• It can help organizations meet data governance requirements by breaking data silos.

Pitfalls to Avoid during Data Replication

While there are many benefits of data replication, you should consider some of its drawbacks while planning your strategy.

• Inconsistency in Data: Data replication from various sources is a complex process. If not tracked and controlled, the replication process can cause some datasets to be out of sync with others. Possible errors include anomalies in data schema, null counts, and more. If not corrected, over time, this can create vast inconsistencies between different data sets. 
• Loss of Data: There is a possibility of data loss during replication from one instance to another. Data loss could happen for many reasons, such as network or hardware failures, software bugs, or even human error. You could also lose data if the data replication tool does not support certain data types or lacks real-time synchronization capabilities.
• Rising Costs: Replicating data to multiple locations will need an increase in storage capacity, increasing costs for the organization. Data replication is a complex and expensive process that requires specialized teams and infrastructure. While its benefits usually outweigh the costs, organizations must be aware of the extra resources needed.
• Increased Load on Networks: Managing data across multiple locations will put pressure on your network and, unless planned for, can take up significant processing capacity. This is where an efficient, customized data replication process can help. 

Best Practices to Follow during Data Replication

To ensure that your organization makes the best use of data replication and avoids facing the common problems mentioned earlier, adopt these data replication best practices.

Select the Right Method of Data Replication

There are three main methods of replicating data, each with advantages and disadvantages, so choose the one that meets your needs best. Start by documenting what data you wish to replicate and why. Your choice would depend on factors like the size of the data, the replication locations, the criticality of real-time updates, and the resources available.

• If you need to create exact replicas of small datasets across geographies, you should consider full table data replication, even though it takes longer and is more complex.
• If you have varied data types that see real-time updates, and store data based on unique keys or IDs, you might prefer key-based incremental data replication. This is more efficient and faster than full table data replication. 
• If your data is stored in relatively static databases, and you don’t foresee significant changes in the source structure, you could opt for log-based incremental replication. This is the most efficient method and is supported by databases like MySQL, PostgreSQL, and Oracle. 

Test the Replication Process Regularly

It is important to test your data replication process before launch and periodically afterward. You should test for the parameters stated below.

• Performance: Measure the time taken for replication, the amount of data replicated, and its impact on your network. 
• Recovery: Check the ability of the replication process to recover data on the primary data system by simulating a shutdown or failure of the latter. 
• Restore: Ensure that your data replication can restore data from a backup in case of any disaster scenarios.
• Failover: Test the ability to fail over to the secondary system in case of a shutdown of the primary system.
• Security: Ensure that data is encrypted during replication and is not accessible to unauthorized persons.

Needless to say, you should carry out these tests in a controlled manner outside the production environment. Proper testing is one of the most crucial data replication best practices to avoid data loss.

Monitor the Data Replication Process

Ongoing monitoring of data replication can show you any issues as they arise, helping you avoid surprises. You should track the following aspects of data replication:

• Status: Track your data pipelines to ensure that the data replication process is running as expected and is not paused or stopped. 
• Consistency: Check that the data is being replicated correctly, without losses, and without issues like unexpected schema changes, anomalies in tables, irregular data volumes, etc. 
• Latency: Track the time taken for data replication and whether it meets your expectations. 
• Error logs: Data replication tools will provide you with error logs and alerts that you should watch to stay on top of any problems as they arise. 
• Resource usage: You should track the network and data storage usage (e.g., bandwidth and disk space) to ensure that data replication is not affecting their performance. 

You can monitor the process using the in-built capabilities of your data replication solution or with a third-party tool for data monitoring. Hevo’s Smart Assist can monitor your data pipelines and proactively alert you about errors or situations that could affect your replication process.

Use Encryption

Ensure that your data replication tool doesn’t make you vulnerable through security or privacy flaws. Encryption of data through the replication process will prevent unauthorized access. Modern-day data replication solutions like Hevo Data keep your data encrypted and safe with their SOC II, GDPR, and HIPAA-compliant systems. 

Factor in the Costs

As mentioned earlier, data replication is a complex process that requires an investment of resources – time, people, and money. Before you launch a new replication project, work out the additional storage requirements that replication will create and their associated costs. If you plan to build your replication process manually, also include the costs of hiring teams to manage the infrastructure. 

Use a Reliable Data Replication Tool

While your in-house engineering team could build and maintain a data replication process, this approach poses challenges. You will need a dedicated team that writes and maintains code, tracks ongoing replication for errors, refactors code every time an API changes, and works out scalability issues. 

One of the key data replication best practices in modern data-driven organizations is the use of data replication solutions that provide benefits like automapping, deduplication, data monitoring and alerts, and scalability. No-code solutions such as Hevo Data provide complete visibility and control over your data while helping you optimize costs. 

Learn how Deliverr used Hevo Data’s no-code solution to replicate 2X more data reliably and automatically while saving 80 hours a month!

Final Thoughts

Data replication is an essential activity today in any data-driven organization, and its advantages easily outweigh the costs. By following data replication best practices, organizations can ensure that their data is utilized in the best possible way. We recommend choosing the right data replication method for your needs, testing and monitoring data replication, factoring in the extra costs, using encryption, and picking a reliable data replication solution. 

A complex and resource-intensive process like data replication can be managed effectively through an automated no-code solution like Hevo Data. 

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