Data replication is the process of copying data from one location to another, often used to enhance data reliability, accessibility, and speed across organizations by employing ETL tools or custom engineering solutions. This practice is essential for data teams to ensure data availability for analytics, data modeling, and reporting, especially when data needs to be disseminated across various departments or geographic regions. While batch processing is often preferred for its cost-effectiveness in non-real-time scenarios, streaming methods offer real-time data replication at a higher cost. Despite its advantages, replication poses risks of data loss or corruption, which tools like Datafold mitigate by providing cross-database data diffing capabilities. This enables teams to verify the integrity of replicated data efficiently, reducing the need for manual checks and ensuring data consistency across systems.