Batch Replication
Batch replication is a data synchronization technique where data is transferred in discrete groups or batches at scheduled intervals, rather than in real-time. It involves collecting changes over a period, processing them as a unit, and applying them to a target system, often used for data warehousing, reporting, and backup scenarios. This approach contrasts with continuous replication methods like change data capture (CDC) or streaming replication.
Developers should use batch replication when dealing with large volumes of data where real-time synchronization is not required, such as in ETL (Extract, Transform, Load) processes for data analytics, nightly database backups, or syncing data between systems with high latency. It is ideal for scenarios where data consistency can tolerate some delay, reducing system load and network overhead compared to continuous methods.