4 Must-know Advantages of Data Replication

• January 25th, 2023

ADVANTAGES OF DATA REPLICATION FI

In a data-driven economy, having higher availability and better accessibility to data can provide a competitive advantage. Therefore, organizations must understand the importance of data replication strategies to build a robust data distribution environment. With data replication, organizations can streamline the process of managing data for backups and analytics.

An automated data replication process is particularly essential for data-driven organizations as they produce a colossal amount of digital information daily. However, the advantages of data replication are not limited to companies that handle a plethora of data. Different data replication strategies can be embraced based on the requirements to manage data efficiently.

What is Data Replication?

Data replication is the process of copying data and storing it in separate nodes, databases, or locations. This is done to ensure the availability and integrity of data in the event of a system failure or other disruption. Data replication can be performed between two on-premise systems, cloud-based databases, and more. This replication can take place in bulk, in scheduled batches, or in real-time across data centers.

Source: Databand

What are the Advantages of Data Replication?

Other than disaster recovery, when implemented efficiently, data replication can provide several benefits to organizations, and IT end users. Some of the advantages of data replication are:

  • Better Data Availability: Guarantees that multiple copies of data are available 24/7/365. This implies that even if the system fails or there is some form of interruption, the data is still accessible from another location. As a result, it maximizes data availability while decreasing downtime.
  • Faster Data Access: By having multiple copies of data stored in different locations, data replication can reduce latency, especially for users accessing data from faraway locations. For example, users in Asia may experience high latency when accessing data from North American data centers. But placing a copy of the data closer to users’ location can improve access times. Also, this minimizes the pressure on single servers and improves overall network speed.
  • Reporting and Analytics: Data replication enables advanced analytics by synchronizing and consolidating data from various sources into data warehouses for business intelligence and machine learning. Real-time insights can be gained for better decision-making by immediately copying data to other locations.
  • Foolproof Security: Creating multiple backup copies improves data security and enables faster disaster recovery. This is important in systems that primarily handle sensitive or critical data. Data replication can also be used for data archiving, which helps keep a historical record and comply with legal, regulatory or audit requirements.

Types of Data Replication & Their Real-World Use Cases

Today, organizations use several types of data replication methods based on the use cases and advantages of data replication. Some of them are:

Synchronous Replication

Synchronous replication makes real-time copies of data. This replication technique is commonly utilized in mission-critical applications that require a significant degree of data availability and consistency. Also, it is employed to achieve low Recovery Time Objectives (RTOs). Although continually replicating data in real-time is relatively expensive, synchronous replication is exceptionally dependable in the case of a disaster.

One real-world instance of synchronous replication is a bank that uses a database management system (DBMS) to establish synchronous replication between a primary database and one or more subsidiary databases. The primary database processes all transactions, including account transfers, deposits, and withdrawals. Concurrently, when the primary database is updated, the secondary databases are instantly modified with the required information. By doing this, the consistency of the data across all databases is guaranteed. For financial institutions, this is important since it ensures that all transactions are accurately and promptly recorded and that consumers can access their account information and conduct transactions whenever they want.

Asynchronous Replication

When using asynchronous replication, data is first saved in the main source. Then, depending on how it’s configured, the data is copied to another location at specific times. Because users can schedule the replication at any time, the network is less congested during peak hours. 

Healthcare organizations use asynchronous replication to ensure the availability of backed-up patient data across different departments. For instance, doctors, technicians, and nurses may need access to patient data from EHRs, lab reports, etc. Using asynchronous replication, patient data can be collected and uploaded to the primary server and replicated as a backup on multiple servers spread across the hospital. This enables data to be viewed by various departments and used to create reports for diagnosis to improve patient care.

Snapshot Replication

Snapshot replication is the process of creating a snapshot of the source database at static points in time and replicating the data in the secondary systems. Unlike most replications, snapshot replication does not keep track of modifications to the data. Consequently, the data gets replicated in a single transaction. Snapshot replication is effective when data doesn’t change regularly or when big changes happen quickly. 

Snapshot replication works best when there are infrequent data changes. For example, if an organization occasionally changes its website, it is advised that the complete snapshot of data be replicated once it has changed. Based on the frequency of the changes to the website, the organization can use snapshot replication weekly or monthly.

Merge Replication

In merge replication, data from two or more databases are consolidated into a single database. It enables both the publisher (the primary server) and subscriber (the secondary server) to independently make updates to the database. This feature makes merge replication the most complicated type of replication. In this case, the initial synchronization from the publisher is a snapshot replication. However, as soon as the data is altered, the altered data is transmitted to a merging agent (installed on all servers). This agent then updates and distributes the data using conflict resolution strategies.

Merge replication can be used for a multi-store retail chain with a central database at its headquarters. Each store can have a local database for tracking sales, inventory, etc. The retail chain can use it to recurrently synchronize the data between the local and central databases at the corporate headquarters. This enables alterations made at one store to be replicated in the databases of the other stores. It also gives the headquarters a complete view of sales, inventory, and customer information for all locations. 

Disadvantages of Data Replication

There are several benefits of data replication, like improving efficiency and guaranteeing data availability. However, it is possible that users may encounter some data replication issues because of certain drawbacks associated with the process. Some of these disadvantages of data replication are:

  • Data Inconsistency: Contrary to centralized environments, managing simultaneous updates in distributed environments is more challenging. When data is replicated from many sources at various times, certain datasets may go out of sync with others. This could happen momentarily, continue for several hours, or result in the data being unsynchronized. 
  • Slow Writing: Although placing secondary data locations closer to consumers makes data access easier, there is a tradeoff. Running data replication at several places simultaneously might strain your network, slow it down, and use up a lot of processing resources. Writing to databases would take longer, even though reading data from dispersed locations is quicker. This can be a problem for organizations with limited bandwidth or high network usage.
  • Version Control: It is not easy to keep track of several replicated data versions, especially when different copies of the same data are being replicated at once. Trying to determine which version of the data is the most recent or reliable may cause inaccuracies. Though version numbering can address this problem to a certain extent, it adds to the workload.
  • Increase Storage Cost: As the name suggests, data replication makes multiple copies of the original data, which might consume a lot of storage space. This is especially true for large-scale systems that produce massive amounts of data. Organizations could incur higher storage expenses due to the extra space needed to keep multiple copies of data. This can be a major concern for businesses with limited storage space or working on a tight budget.
  • Database Coupling: In the context of data replication, data coupling refers to the strict integration of the replication process with the underlying DBMS. This implies that the replication process is closely intertwined with the particular database in use. As a result, it is impossible to modify or replace the database without changing the replication method. This can affect the flexibility and scalability of the entire business process.

Conclusion

Organizations can benefit by offering accessible data to every end-users by implementing data replication in a distributed environment. Though there are multiple types of data replication, each has its own advantages and disadvantages. Before incorporating a data replication strategy, ensure you are familiar with your business needs and the benefits of every data replication type. 

These data replication strategies, however, are quite effort-intensive and require in-depth technical expertise. Implementing them can be challenging especially for a beginner & this is where Hevo saves the day!

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