Migration Paths

Our research covers 35 distinct migration paths spanning mainframe modernization, cloud replatforming, database migrations, language conversions, and infrastructure transitions. Each path includes median cost ranges derived from real project data, success rate benchmarks aggregated from post-implementation reviews, complexity assessments calibrated against team size and codebase scope, and timeline estimates grounded in actual delivery schedules rather than vendor projections. Where available, we include ROI timelines and cost avoidance figures that procurement teams can use directly in business case development.

The migrations are organized by hub category — thematic groupings such as mainframe modernization, cloud migration, and database modernization — so that teams evaluating adjacent paths can compare trade-offs side by side. For example, an organization considering moving off a mainframe can compare COBOL-to-C#, COBOL-to-Java, and mainframe-to-cloud rehosting paths within the same hub, each with independent cost and success data. This structure reflects how modernization decisions are actually made: not in isolation, but as a choice among competing approaches with different risk, cost, and timeline profiles.

Every migration path is reviewed against a standard framework that includes decision criteria (when to pursue the path and when not to), alternative approaches, AI-assisted tooling options, vendor landscape analysis, and evaluation questions for RFP processes. The goal is to provide the kind of structured, comparable data that engineering leaders and procurement teams need to make informed decisions — replacing anecdotal vendor claims with aggregated, source-backed intelligence. Success rates, cost ranges, and timelines are presented as ranges rather than point estimates to reflect the inherent variability across organizations of different sizes, industries, and technical maturity levels.

Data is updated on a rolling basis as new case studies and vendor disclosures become available. Each path notes its last review date and the number of projects analyzed, so readers can assess recency and sample size independently. We prioritize depth over breadth: every migration included here has sufficient real-world data to support actionable guidance, rather than speculative coverage of emerging paths without track records.