Row-based ETL pricing models conceal hidden costs such as duplicate processing, unchanged record syncing, and development retries, leading to inflated bills that often do not reflect actual data value. Shifting to performance-based pricing aligns costs with real infrastructure usage, enabling predictable budgeting, greater efficiency, and funding for innovation.
This blog summarises a LinkedIn Live session addressing how data teams can reduce ETL costs without compromising productivity or rushing into platform migrations. Drawing on insights from experienced industry leaders, it outlines strategies for improving cost visibility, minimising engineering friction, and approaching migration decisions with a structured, value-led plan rather than reactive urgency.