Replication is the process of creating and managing duplicate versions of a database. Replication not only copies a database but also synchronizes a set of replicas so that changes made to one replica are reflected in all the others.
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Benefits of replicating data
Replication enables many users to work with their own local copy of a database but have the database updated as if they were working on a single, centralized database. For database applications where users are geographically widely distributed, replication is often the most efficient method of database access.
Although replicating does incur processing and storage space costs, it offers significant benefits to businesses, IT professionals, and end-users alike. Here are some of the benefits of replicating data:
Improved reliability and availability: Data replication improves the reliability of systems while copying and storing the data at multiple locations across the networks. It helps users to access the data without any failure, even if technical glitches occur to the user systems or networks due to hardware failure, cyber-attacks, and other software disruptions.
Enhanced network performance: Data replication allows users to direct their data reads across multiple servers in a distributed system. It reduces the load on the primary server by routing all data read operations to replicate the database and can save the primary server for the operations that require more processing power.
Increased data analytics support: The continuous data replication process that occurs between a production database and data warehouse helps business intelligence teams analyze data quickly and make insightful business decisions.
Improved test system performance: IT administrators can access data to test system performance more easily using data replication tools. They can optimize the synchronization and distribution of data across the systems and networks for speed, reliability, responsiveness, and stability of a system, network, or application.
Challenges of replicating data
While providing many benefits, data replication does present several challenges in terms of cost, inconsistency, and more. Following are some of the biggest challenges:
Increased costs: Replicating or copying data to multiple locations requires more storage space and processor costs. Additionally, it may require the effort of a dedicated IT team. The bigger the business, the bigger would be the costs incurred with the replication process.
High implementation and management time: Implementation and management can be time-consuming. Depending on businesses’ replication needs, it may take months to implement and copy the data without any failure. Further, storing the data of large-scale businesses at multiple locations may need the patience of all stakeholders.
Ensuring consistency: Maintaining consistency across all distributed environments during the process of updating replica files is a tedious task and may require more bandwidth. Therefore, the users can be out of data for a temporary period or a few hours if the IT administrators are not carefully planning and implementing the replication process.
When it comes to data replication, three key methods are employed: full-table, key-based incremental, and log-based incremental. Understanding each method can help the end-users or businesses to decide which method is more suitable for their needs.
Full-table replication: As the term implies, full-table replication copies every piece of data, including existing, new, and updated information and all tables, from the original database to the destination source. Compared to other methods, it requires more storage space and processing power, and it also results in heavier stress on networks.
Key-based incremental replication: Key-based incremental replication is one of the most often-used replication methods in which only the data that was changed since the last update replicates. Although it’s more efficient and uses less processing power than the full-table replication method, it fails to replicate hard-deleted data from the original database.
Log-based incremental replication: Log-based incremental replication is a method in which data replication works based on the database log file. Therefore, the log files of the source database need to be updated all the time. Even though it’s the best method to apply, the main drawbacks of the log-based incremental replication method include the time-consuming process of log file updating and it can only apply to the source database.
There are different types of replications, and each type has its own performance value and acceptance among businesses and IT professionals. Here are some of them:
Database replication: Database replication is a type of replication process mainly used in most Database Management Systems (DBMS). When an update takes place in the primary database, each replica updates successfully without any separate actions as it’s a type of multi-master database replication, in which the update submitted in any database node can ripple through to all replicas.
Disk storage replication: Disk storage replication is the process of replicating data available over a network to different locations. It involves more than one storage device that is connected physically or via Storage Area Network (SAN). It improves the availability and accessibility of data in real-time even when an unexpected failure occurs. However, it requires a high implementation and management cost.
File-based replication: In file-based replication, data replication carries out at the logical level, i.e., individual data files, rather than the storage block level. There are various methods to conduct file-based replication, which include copying with a kernel driver, file-system journal replication, batch replication, and more.
Distributed shared memory replication: In the process of distributed shared memory (DSM) replication, replicate the data to different nodes. The DSM also keeps a track of nodes where the data is copied. It ensures the availability of the data as multiple nodes has read access.
Primary-backup replication: The primary-backup replication involves a primary database and one or two backups. The primary performs all computational and updates processes. These changes and updates ripple to the backups later. In this type of replication, any failure to the primary cannot handle as easy as backups.
Top replication software
Given the importance of team access to database-based applications, businesses use replication software to ensure the availability of and speedy access to data that’s up to date.
Acronis: As AI-based replication software, Acronis allows users to replicate their data over 20 platforms while protecting against ransomware attacks or any other failure. Multiple plans are available starting at $119/ annually.
Zerto: Zerto facilitates a rapid replication process between the primary database and other secondary databases. With its robust features, users can easily carry out database consolidations as well as data migrations. Zerto also offers a 14-day free trial to allow users to get more familiar with its features and functionalities.
Veeam: Veeam is powerful and automated replication software that helps reduce the workloads of virtual as well as physical systems and networks.
NAKIVO, Qlik, EMC RecoverPoint, IBM Informix, Fivetran, CouchDB, SharePlex, Oracle GoldenGate, DBSync, and Lytron are other significant replication applications that businesses use for replication and disaster recovery.