Improve AWS DMS continuous replication performance by using column filters to parallelize high-volume tables

This article discusses how to improve AWS Database Migration Service (DMS) continuous replication performance by using column filters to parallelize high-volume tables. The key approaches include:

• Creating a temporary immutable column to divide large tables into multiple CDC (Change Data Capture) tasks
• Addressing challenges like high latency, data loss risk, and resource strain during database migrations
• Using a modulus operation to split a table into evenly distributed groups
• Creating multiple AWS DMS tasks with column filters to process different data segments
• Demonstrating performance improvements by reducing target migration latency

The solution provides a method to optimize database migration for tables with frequent updates by enabling parallel processing and reducing overall migration time and resource consumption.