A World Leader in Aircraft Engines migrates from Greenplum to Amazon Redshift
A World Leader in Aircraft Engines migrates from Greenplum to Amazon Redshift
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What Next Pathway's A World Leader in Aircraft Engines Case Study covers
A World Leader in Aircraft Engines migrated Greenplum to Amazon Redshift in just 6 weeks. Next Pathway’s automation platform translated 500 complex stored procedures and more than 70 views, achieved 72% faster migration acceleration over manual approaches, and enabled automated high quality code conversion with rigorous QA testing.
Accelerated Greenplum to Redshift Migration
Next Pathway supported the migration of a large Greenplum data warehouse environment to Amazon Redshift for a global aircraft engines and avionics company. The initial engagement focused on translating 500 highly complex stored procedures to demonstrate migration speed and feasibility.
Automated Translation and Quality Assurance
Within just 6 weeks, Next Pathway translated all 500 stored procedures and more than 70 views using its automated migration platform. All translated code was validated through a rigorous 4 point QA unit testing process to ensure complete and high quality conversion accuracy.
Proven Migration Acceleration
The results demonstrated a 72% acceleration compared to manual migration approaches, validating the effectiveness of Next Pathway’s automated migration methodology. Following the successful pilot, the company awarded Next Pathway the remaining Greenplum code base migration to Amazon Redshift.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
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Amazon Redshift Migration Guide
Accelerate your migration with automated code conversion, validation, and proven migration best practices.
What Industry Analysts Say
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ENDERLE GROUP
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THE BLOOR GROUP
What a structured Amazon Redshift migration covers
A successful migration to Amazon Redshift requires a clear strategy across four critical phases.
Discovery and dependency mapping
Identify databases, SQL objects, ETL pipelines, BI reports, and data dependencies before migration begins. Complete visibility helps eliminate hidden risks and enables accurate migration planning.
Code translation and modernization
Convert legacy SQL, stored procedures, ETL workflows, and scripts into optimized Amazon Redshift-compatible code. Automated translation reduces manual effort while improving consistency and speed.
Validation and functional parity
Validate migrated workloads against the source environment to ensure data accuracy, query consistency, and business functionality before production deployment.
Production cutover planning
Execute a controlled cutover with rollback planning, workload scheduling, stakeholder approvals, and post-migration monitoring to minimize business disruption.
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