What is Data Replication?: The Ultimate Guide 101

on Data Integration, Data Replication, Database, ETL, Tutorials • March 8th, 2022 • Write for Hevo

Data Replication | Hevo Data

One of the biggest challenges that most organizations face today is ensuring high availability and accessibility of data over the complex set of networks they have in place. Having around-the-clock and real-time access to crucial business data can help organizations carry out processes seamlessly and maintain a steady revenue flow. Organizations, thus have a growing need to scale their systems & provide the support for accessing data seamlessly. Data Replication is one such technique.

Data Replication allows users to access data from numerous sources such as servers, sites, etc. in real-time, thereby tackling the challenge of maintaining high data availability. This article aims at providing you with in-depth knowledge on what is Data Replication and its advantages & disadvantages.

Upon a complete walkthrough of the content, you’ll have a great understanding of what Data Replication is all about and why you must start replicating and maintaining your crucial business data.

Table of Contents

What is Data Replication?

Data Replication refers to the process of storing and maintaining numerous copies of your crucial data across different machines. It helps organizations ensure high data availability and accessibility at all times, thereby allowing organizations to access and recover data even during an unforeseen disaster or data loss.

There are multiple ways of Data Replication, namely, Full Replication, which allows users to maintain a replica of the entire database across numerous sites, or Partial Replication, which lets users replicate a small section/fragment of the database to a destination of their choice.

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Hevo Data can be your go-to tool if you’re looking for Data Replication. It supports various kinds of Replication such as Logical, Streaming, etc. with its No-Code interface. Hevo offers compatibility of integrations from 100+ Data Sources (including 40+ Free Data Sources) into Redshift, Snowflake, and other Databases and Data Warehouses. Try Hevo if you’re looking for an all-in-one package. To further streamline and prepare your data for analysis, you can process and enrich Raw Granular Data using Hevo’s robust & built-in Transformation Layer without writing a single line of code!

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How does Data Replication work?

Data Replication is the process of writing or copying the same data to multiple locations. Data can be copied between two on-premises hosts, among hosts in various locations, too numerous storage devices on the same host, or to and from a cloud-based host, etc. Data can be copied on demand, transferred in batches or in bulk according to a schedule, or replicated in real-time as the data in the master source is written, changed, or deleted.

What are the Benefits of Data Replication?

Replicating data and maintaining multiple copies of data across various servers provides users with numerous benefits such as robust performance, data security, data durability, etc. The following are some of the key benefits of Data Replication:

1) Better Application Reliability

Data Replication across various machines helps ensure that you can access the data with ease, even when a hardware or machinery failure occurs, thereby boosting the reliability of your system.

2) Better Transactional Commit Performance

When you’re working with transactional data, you need to monitor various synchronous processes to ensure that the data updation takes place everywhere at the same time. Hence, your application must write the commit before the control threads can continue the tasks.

Data Replication helps avoid such additional disk-based I/O operations by eradicating the data dependency on the master node only, thereby making the entire process more durable.

3) Better Read Performance

With Data Replication in place, users can route data reads across numerous machines that are a part of the network, thereby improving upon the read performance of your application. Hence, readers working on remote networks can fetch and read data with ease.

This application of Data Replication also helps reduce the cache missings & lower the input/output operations on the replica as replicas may also need to cache that part of the data.

4) Data Durability Guarantee

Data Replication helps boost and ensure robust data durability, as it results in data changes/updation taking place on multiple machines simultaneously, instead of a single computer.

It thereby provides more processing & computation power, by leveraging numerous CPUs and disks to ensure that the replication, transformation, and loading processes take place correctly.

5) Robust Data Recovery

Organizations depend on a diverse set of software and hardware to help them carry out their daily operations and, hence fear any unforeseen data breaches or losses. Data recovery is thus, one of the biggest challenges and fears that all organizations face.

Replication allows users to maintain backups of their data that update in real-time, thereby allowing them to access current and up-to-date data, even during any failures/ data losses.

What is the Data Replication Process?

Now that you’re familiar with what is Data Replication, let’s discuss the replication process in brief. Most in-use enterprise-grade databases such as MongoDB, Oracle, PostgreSQL, etc., house the support for replicating data with ease.

These databases allow users to copy data, either by leveraging the in-built replication functionalities or using third-party tools to achieve replication. In either case, the general process of replicating data remains identical.

The following process represents the general steps a user needs to carry out to replicate data properly:

  • Step 1: The first step of replicating data is identifying your desired data source and the destination system, where you’ll store the replica.
  • Step 2: Once you’ve decided on your data source and destination, you need to copy the desired database tables and records from your source database.
  • Step 3: The next important step is to fix the frequency of updates, that is how frequently you want to refresh your data.
  • Step 4: With the replication frequency now decided, you now need to choose the desired replication mechanism, selecting between Full, Partial or Log-based.
  • Step 5: You can now either develop custom code snippets or use a fully-managed data integration & replication platform such as Hevo Data, to carry out replication.
  • Step 6: With the Data Replication process happening, you need to keep track of how the data extraction, filtering, transformation, and loading is taking place to ensure data quality and seamless process completion.

Why does Data Replication Matter?

Data plays an important role for companies, and the data stored in the Databases must be accessible to its users when needed without any lag. For this, Data Replication to different servers is vital because if one of the primary servers fails then another replica server can be used without disrupting the data access.

Also, it helps in keeping the backup of data to avoid any data loss at times of disaster. Data Replication helps in the following:

  • Optimize the server and the network performance.
  • Perform Data Analytics to advance Business Intelligence.
  • Share dame data across users and different locations without inconsistency.

What are the Most Common Types of Data Replication?

The common types of Data Replication processes are listed below: 

  • Full Table Replication: Full-time replication copies all the data from the source system to the destination. It consists of existing rows, and updated rows and, also replicates the hard deletes. The disadvantage of Full-time replication is that it puts a burden on the network and takes time if the dataset is large.
  • Transactional Replication: In Transactional Replication, first all the existing data is replicated to the destination. Then, as a new row comes into the source system, it replicates it immediately to the destination. This ensures transaction consistency.
  • Snapshot Replication: Snapshot Replication takes a snapshot of the source system at the time of replication and then replicates the same data to all the destinations. It does not consider any changes in data during replication.
  • Merge Replication: Merge Replication merges two or more Databases into a single Database. It is one of the complex types of Data Replication. This Data Replication type is used when the data is distributed across multiple data sources and wants to unify and synchronize data in one place so that all users can use it.
  • Key-based Incremental Replication: In Key-based Incremental Replication, the first keys are scanned and checked if any index is added, deleted, or updated. Then, only relevant keys or indexes are replicated to the destination making the backup process faster.

What makes Hevo’s Data Replication Experience Best in Class?

Manually performing the Data Replication process can be a tiresome task without the right set of tools. Hevo’s Data Replication & Integration platform offers Real-time Replication and empowers you with everything you need to have a smooth Data Collection, Processing, and Replication experience. Our platform has the following in store for you!

  • Exceptional Security: A Fault-tolerant Architecture that ensures Zero Data Loss.
  • Built to Scale: Exceptional Horizontal Scalability with Minimal Latency for Modern-data Needs.
  • Built-in Connectors: Support for 100+ Data Sources, including Databases, SaaS Platforms, Files & More. Native Webhooks & REST API Connector available for Custom Sources.
  • Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility ~ designed for everyone.
  • Smooth Schema Mapping: Fully-managed Automated Schema Management for incoming data with the desired destination.
  • Blazing-fast Setup: Straightforward interface for new customers to work on, with minimal setup time.

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What are Data Replication Schemes?

There are mainly 2 Data Replication Schemes used for Database Replication. The following Data Replication Schemes are listed below:

1) Full Database Replication

Full Replication involves copying the complete Database to every node of the distributed system. With this, users can achieve high data redundancy, better performance, and high data availability. It takes a long time because data updates need to replicate to all the nodes.

2) Partial Replication

Partial Replication copies only a particular part of the Database that is decided based on the business requirements or priority. The number of copies for each part of the Database can range from one to the number of total nodes in the distributed system.

What are the Components of a Data Replication Network?

Let’s also read about important components of the Data Replication Network apart from publishers and subscribers.

Distributor

The distributor is a server in the Replication network that is responsible for managing the distribution Database and storing all the history, transactions, snapshots, and metadata of all the replication.

There are 2 types of distributors – local distributor which is the same as publisher server. The other is a remote distributor which is used single distributor that caters to multiple publishers.

Replication Agents

Replication Agents are the programs that are responsible for performing various tasks such as detecting and updating publisher and subscriber data, making copies, etc. They are the most essential part of the replication process. Some of the replication agents run from the distributor are:

  • Snapshot agent
  • Distribution agent
  • Merge agent
  • Log Reader agent
  • Queue reader agent

What to Consider When it Comes to Data Replication?

While you are replicating data on-premise data to Cloud, across multiple Cloud environments, or bidirectionally. It is essential to keep the point of a few factors, listed below:

  • How to reign in network and storage costs 
  • How to minimize the impact on production workloads

First, it is essential to minimize the storage requirements and cost of operating the data. It is recommended that one should deduplicate the data before performing a Data Replication process that can be automated.

The wide area network (WAN) connections deliver fast speed with little impact on production workloads. Also, you should have good knowledge of whether your company needs synchronous or asynchronous Data Replication.

The Synchronous Data Replication process writes data to its primary storage and to its replica server at the same time. This will allow you to replicate the data but it comes with 2 major drawbacks that are time and cost.

To replicate data it is essential to confirm that all the data is written properly. It decreases the network performance significantly and increases the cost.

The Asynchronous Data Replication process writes data to the replicas after it has been written to the primary storage. Once the storage device finishes receiving the data, the write operation is considered to be complete. It requires less bandwidth for the network and is designed to work for long distances. 

What are the Challenges of Replicating Data?

Data Replication provides users with numerous benefits that help boost performance and ensure data availability. However, it also poses some challenges to the users trying to copy their data. The following are some of the challenges of replicating your data:

1) High Cost

Replicating data requires you to invest in numerous hardware and software components such as CPUs, storage disks, etc., along with a complete technical setup to ensure a smooth replication process.

It further requires you to invest in acquiring more “manpower” with a strong technical background. All such requirements make the process of replicating data, challenging, even for big organizations.

2) Time Consuming

Carrying out the tedious task of replication without any bugs, errors, etc., requires you to set up a reaction pipeline. Setting up a reaction pipeline that operates correctly can be a time-consuming task and can even take months, depending upon your replication needs and the task complexities.

Further, ensuring patience and keeping all the stakeholders on the same page for this period can turn out to be a challenge even for big organizations.

3) High Bandwidth Requirement

With replication taking place, a large amount of data flows from your data source to the destination database. To ensure a smooth flow of information and prevent any loss of data, having sufficient bandwidth is necessary.

Maintaining bandwidth, capable of supporting & processing large volumes of complex data while carrying out the replication process can be a challenging task, even for large organizations.

4) Technical Lags

One of the biggest challenges that an organization faces when replicating its data is technical lags. Replication usually involves leveraging master nodes and slave nodes. The master node acts as the data source and represents the point where the data flow starts and reaches the slave nodes.

These slave nodes usually face some lag associated with the data coming from the master node. Such lags can occur depending upon the system configurations and can range from a few records to hundreds of data records.

Since the slave nodes often suffer from some lag, they often face delays and do not update the data in real-time. Lags are a common issue with most systems and applications. However, they can be quite troublesome in cases as follows:

  • In case you’re shopping on an e-commerce website, and you add products to your cart, but upon reaching the checkout stage, the “products” disappear. This happens due to a lag in replication in the slave node.
  • In case you’re working with a transactional data flow, the transactions you might have made are taking time to reflect at the destination. This happens due to a lag in replication in the slave node.

Hevo can abstract all these challenges with its automated No Code Data Pipeline. With Hevo in place, you can perform Data Replication seamlessly. Hevo has fault-tolerant architecture making your Data Replication process secure, fast, and reliable.

Data Replication FAQs

1) What is data replication storage?

Storage-based replication, also known as data replication storage, is a method of replicating data available over a network to multiple distinct storage locations/regions.

2) Why does data replication matter?

Any loss of data, whether due to system failure, connectivity failure, or disaster, can result in significant losses. Companies opt for Data Replication to avoid these losses.

Data Replication facilitates large-scale data sharing among systems and distributes network load among multisite systems by making data available on multiple hosts or data centers.

3) What are the types of data replication?

The different types of data replication are as follows:

  1. Full-table replication: Full-table replication copies every new row, updated row, and existing row from the source storage to the destination storage. In simple terms, it copies everything from the source storage to the destination
  2. Snapshot replication: Snapshot replication takes a “snapshot” of the source database during replication and replicates it to all destination databases.
  3. Merge replication: Merge replication is the process of combining two or more databases into a single database.
  4. Key-based incremental replication: One of the most popular types is key-based incremental replication. Before starting replication, the replication process scans keys (or indexes in a DBMS) to see which ones have changed (deleted, new, updated). The process then replicates only the relevant replication keys, resulting in a much faster backup.
  5. Transactional replication: Transactional replication copies all existing data from the source to the replicas first. The same transaction is then executed in the replicas with each new transaction in the source, ensuring transactional consistency.
  6. Log-based incremental replication. Transactional operations are sometimes implemented as log-based incremental replication, and other times log-based replication is used as a stand-alone solution. The log files of the source database are scanned in the log-based incremental implementation, the change data capture approach identifies which rows have changed, and the same changes are implemented in the destination database.

4) What is the difference between data replication and data backup?

The act of copying and then moving data between a company’s sites is known as Data Replication. It is commonly measured in terms of Recovery Time Objective (RTO) and Recovery Point Objective (RPO) (RPO). It focuses on business continuity or the continued operation of mission-critical and customer-facing applications following a disaster.

Data backup continues to be the go-to solution for many industries that require long-term records for compliance and granular recovery.

How does HEVO help in Data Replication?

Hevo Data, a Fully-managed Data Pipeline platform, can help you automate, simplify & enrich your data replication process in a few clicks. With Hevo’s wide variety of connectors and blazing-fast Data Pipelines, you can extract & load data from 100+ Data Sources including straight into your Data Warehouses or any Databases. To further streamline and prepare your data for analysis, you can process and enrich raw granular data using Hevo’s robust & built-in Transformation Layer without writing a single line of code.

Hevo is the fastest, easiest, and most reliable data replication platform that will save your engineering bandwidth and time multifold. Try our 14-day full access free trial today to experience an entirely automated hassle-free Data Replication.

Conclusion

This article teaches you in-depth about what is Data Replication, its advantages and disadvantages & answers all your queries about it. It provides a brief introduction of numerous concepts related to it & helps the users understand them better and use them to perform Data Replication & recovery in the most efficient way possible.

These methods, 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!

Visit our Website to Explore Hevo

Hevo Data provides an Automated No-code Data Pipeline that empowers you to overcome the above-mentioned limitations. Hevo caters to 100+ data sources (including 40+ free sources) and can seamlessly perform Data Replication in real-time. Hevo’s fault-tolerant architecture ensures a consistent and secure replication of your data. It will make your life easier and make data replication hassle-free.

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