Understanding Enterprise Data Replication: A Comprehensive Guide

on Data Integration, Data Replication, Data Warehouses, Database, Enterprise Data • May 13th, 2022 • Write for Hevo

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In this age of Information Economy, data is generated from every digital computing device, handheld phone, workstation, server, and so on. The amount of data produced every day is truly staggering. Organizations are storing, processing, and analyzing data more than at any time in history.

With so much data flowing in and out of the loop, there has been an ever-increasing pressure on enterprises to scale up their systems to provide robust, secure, and speedier access to data. This is where Enterprise Data Replication comes in.

Nothing can be more terrifying than losing important data in a mine of information. This is often the case when your system suddenly crashes. In addition to that, ensuring high availability is a big challenge when a number of users are simultaneously trying to access the data more frequently.

Well, Enterprise Data Replication is here to save you from all the hardships. Enterprise Data Replication stores the same data in multiple locations to improve data availability and accessibility. This article will take you through various aspects of Enterprise Data Replication.

Table of Contents

What is Data Replication?

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Data Replication is the process of generating multiple copies of datasets and storing them at multiple locations to enhance data availability and accessibility. It basically copies the Primary Database to a Secondary Database as record updates occur. This organized mechanism records and updates even the small changes in the Application Database. After that, the same updates are passed on to the clone Secondary Database as well. By now, you must have got an idea of how Data Replication optimizes data availability.

Additionally, Data Replication plays a crucial role in the Disaster Recovery and Backup Management strategy of an organization. In the event of disasters or crashes, organizations are left with days old of backups of data to rely on. However, with a Data Replication strategy in place organizations can ensure that an accurate backup exists at all times even in case of a catastrophe or system failure.

What is Enterprise Data Replication?

Enterprise applications need highly available Database Systems as they can’t afford any downtime. These applications have a direct impact on the business processes and any downtime can lead to stagnation in the revenue-generating processes. As a result, Enterprise Databases have become extremely important for almost every firm. An Enterprise Database covers all the data stored in an organization and it is important to make that data available at all times. Enterprise Data Replication is aimed at maintaining data availability across heterogeneous environments.

Enterprise Data Replication (EDR) refers to the process of generating numerous copies of enterprise data and storing them in multiple locations. EDR began in tandem with Database Replication, with the goal of transferring data from one Database to another of the same type. However, EDR tools are now capable of replicating data from multiple sources in various types of Databases in a heterogeneous environment.

Key Features of Enterprise Data Replication

Let’s discuss what Enterprise Data Replication brings to your organization.

  • Enterprise Data Replication makes enterprise data available to multiple users across different locations by letting them access the replica closest to them.
  • EDR can help your organization cut costs associated with bandwidth and maintenance.
  • You can easily monitor and configure Data Replication tasks across 100s or even 1000s of endpoints through the UI.
  • EDR triggers a robust and organized mechanism for Disaster Recovery and Backup Management.
  • The end result of Enterprise Data Replication is to help organizations set up effective Data Analytics and Business Intelligence.

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What are Enterprise Data Warehouses?

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A Data Warehouse, also known as the “Single Source of Truth”, is defined as a centralized Data Repository used for Analytical and Reporting purposes. An Enterprise Data Warehouse (EDW) houses data from multiple departments, sources, and applications to make centralized analytics available across an enterprise. This data is generally contributed by on-premises sources such as production apps and physical records, as well as Cloud Sources such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and other web-based applications.

Overall, the data housed within an EDW contains critical information that basically captures a larger view of the entire business. Without a centralized Enterprise Data Warehouse, departments are bound to face challenges working with data silos. Traditionally, Data Warehouses were hosted in on-premises Data Centers. Moving away from the world of traditional and physical Data Centers, Cloud Computing has enabled Serverless, Cloud-based Data Warehouses where the compute and storage resources can be separated and scaled independently.

Examples of Modern Enterprise Data Warehouses include Google BigQuery, Snowflake, and AWS Redshift.

Popular Enterprise Data Replication Strategies 

Data Replication basically copies data from one location to another. Data can be replicated on-demand or in real-time, in bulk or in batches as per a schedule.

There are three basic methods for Enterprise Data Replication:

Full Table Replication

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As the name suggests, Full Table Replication moves basically the entire data including new, updated, and existing data from the source to the target system. This helps in maintaining a full backup in cases where the records are regularly hard deleted from the source.

However, Full Table Replication requires higher processing power and it increases the network loads as it copies entire data instead of just changed data. Copying full tables upsurges your cost as well, as the number of rows copied increases and maintaining consistency becomes difficult.

Advantages

  • It is one of the most robust strategies that copies the entire data from the source and maintains an exact mirror image of the original table.
  • Having exact replicas across different geographies results in faster queries and good throughput time. 

Disadvantages

  • Creating a full copy in each replication requires a lot of bandwidth with respect to processing power, resources, etc.
  • Replicating the entire Database can result in multiple errors and can be a tedious process to accomplish.

Log-Based Data Replication

Most Database-based solutions maintain a record of the changes made in the Database. A log file or changelog is then generated to keep track of everything. Each log file is basically a collection of log messages, each of which contains important information such as the time, user, change, cascade effects, and change method. A unique Position ID is then assigned to each logfile by the Database to store them in chronological order by that Id.

Log-Based Data Replication is viable only for Database Sources as it uses the binary log files in the Database to replicate the data. It pulls data directly from the log files, which reduces the load on the production system. This method is the closest to real-time Data Replication. This technique works best in cases where your Database Source structure is relatively static and doesn’t require frequent changes.

Advantages

  • Replicas perform the various cascading-based changes by using integrity constraints.
  • It allows users to audit with ease.

Disadvantages

  • Updating the log-based system frequently can be a time and resource-consuming process. Hence, it is best suited for a relatively static Database Source structure.

Key-Based Incremental Data Replication

Modern Databases receive and generate updates very frequently in real-time, and the Databases are expected to have varied data requirements. Key-Based Incremental Data Replication uses the Replication Keys to update only the data that has been modified or changed since the last update. The Replication Key column is used to identify the new and updated data. The replication process is then carried out for the records that house the updated replication keys.

As you can see, only fewer rows of data are copied during the replication, hence, Key-Based Replication proves to be much more efficient and faster when compared to Full Replication. However, Key-Based Data Replication proves to be inefficient when replicating hard-deleted data as the key value is deleted when the record is deleted. Key-Based Data Replication is used by enterprise-grade Databases such as PostgreSQL, Oracle, Salesforce, etc., to replicate data with ease.

Advantages

  • Key-Based Incremental Data Replication requires less bandwidth & compute resources as it focuses only on new and modified data.

Disadvantages

  • Key-Based Incremental Data Replication fails to replicate hard-deleted data as it automatically deletes the replication key associated with a record, in case that data record gets deleted.
  • It doesn’t maintain a change record history, and hence, keeping track of the historical values of the new data records can be a challenging task.

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Providing a high-quality ETL solution can be a cumbersome task if you just have lots of data. Hevo’s automated, No-code platform empowers you with everything you need to have a smooth ETL experience. Our platform has the following in store for you!

Check out what makes Hevo amazing:

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  • Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis in a BI tool such as Power BI.
  • Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
  • Scalable Infrastructure: Hevo has in-built integrations for 100’s sources that can help you scale your data infrastructure as required.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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Benefits of Enterprise Data Replication

Here are a few benefits that your organization can have by implementing Enterprise Data Replication.

  • Data Reliability and Availability: Enterprise Data Replication makes sure that the enterprise data is easily accessible across different geographies at all times. Even if one site experiences a hardware failure or issue, data will still be available at other sites.
  • Disaster Recovery: Data Replication plays a crucial role in terms of the Disaster Recovery and Data Protection strategy of an organization. With a Data Replication strategy in place, organizations can ensure that a consistent backup is maintained at all times even in case of a catastrophe or system failure.
  • Server Performance: Data Replication enhances and boosts server performance by allowing easy and quick access to data even when numerous copies are run on multiple servers.
  • Better Network Performance: Having copies of the same data in multiple locations decreases data access latency by accessing the relevant data from the location where the transaction is being conducted.
  • Enhanced Test System Performance: EDR streamlines and simplifies the distribution and synchronization of data for test systems that require faster accessibility for quick decision-making.

Conclusion

Organizations today are overflowing with data. The amount of data produced every day is truly staggering. Trying to manage humongous amounts of data without a proper plan and design is going to be really challenging. That’s a game of data hide and seek you don’t wanna play, and that is why you need Enterprise Data Replication. In simple words, having a replica of your enterprise data ensures high availability and makes data access faster, especially in organizations with a large number of locations.

This article introduced you to Enterprise Data Replication and took you through various aspects of it. However, it’s easy to become lost in a blend of data from multiple sources. Imagine trying to make heads or tails of such data. This is where Hevo comes in.

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