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Data replication is the process of duplicating data across multiple locations to enhance both availability and accessibility. This involves regularly copying data from a database (or other storage systems) to other locations, ensuring that all users have access to the same information. By distributing the data, replication also helps reduce the load on databases, especially those handling transactional operations, where performance is critical. Data replication software simplifies this process by providing tools for integrating, distributing, centralizing, and synchronizing data across various systems and storage locations, enabling businesses to manage increasing data volumes and access real-time information. Replication can be categorized into full replication, where the entire database is duplicated across all sites, and partial replication, where only frequently used portions of the database are replicated. Many data replication tools also offer Change Data Capture (CDC) functionality, which tracks and captures any changes made to the database. These software solutions typically include a graphical interface, allowing users to centrally manage and monitor their replicated data. This makes them valuable for infrastructure teams—whether responsible for servers, virtual machines, or databases—who seek to improve data availability and consistency. While data replication software shares similarities with server backup software in that both involve creating copies of company data, they serve different purposes. Server backups are primarily designed to protect against data loss in disaster recovery scenarios, whereas data replication is broader in scope. It is used to maintain up-to-date copies of data across various databases and servers for a variety of operational needs. Data replication is often used in conjunction with data integration software, which consolidates data from multiple sources into a single repository, and big data processing tools, which enable the real-time collection, distribution, and management of large, unstructured data sets.