A fast-growing MarTech platform was facing challenges with its MySQL infrastructure as rapidly expanding time-series workloads began impacting performance. Query latency was increasing, storage demands were rising, and managing historical data had become increasingly complex. Previous migration attempts using pg_chameleon and Debezium with Kafka proved inadequate due to intricate schema relationships and datatype dependencies. To address these challenges, a custom migration framework was developed to overcome the limitations of off-the-shelf solutions and ensure a seamless transition.