The Definitive Guide to Choosing ETL Platforms for Mainframe Cloud Migration

Mainframe-to-cloud migration can enable AI, real-time analytics, and lower infrastructure costs, but it is complicated by legacy formats such as EBCDIC, COBOL Copybooks, packed decimals, VSAM files, tightly coupled logic, and stringent uptime and regulatory requirements. The material argues that successful ETL platform selection depends on native mainframe connectivity, log-based change data capture, appropriate ETL or ELT transformation capabilities, hybrid agent-based deployment, automatic schema-drift handling, robust security integrations, centralized governance, and predictable pricing. It recommends inventorying data sources and sensitivities, confirming DB2-specific CDC support, projecting future data volumes and costs, validating security requirements, and conducting proof-of-concept testing at two to three times production volume with complex fields, schema changes, recovery scenarios, and latency measurements. It also notes that AI-assisted mapping and SQL translation may reduce migration timelines, while presenting CData Sync as a platform that supports these requirements through mainframe-native replication, open table formats, governance features, and examples of customer deployments.

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