Hadoop Migration Guide
A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to Hadoop Migration faster and with full confidence.
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What Next Pathway's Hadoop Migration Guide covers
A successful Hadoop migration requires a structured, phase by phase approach across discovery, code translation, validation, and cutover. Next Pathway's Hadoop Migration Guide gives your team a complete roadmap, built on the same automation Next Pathway uses to deliver enterprise migrations end to end.
Discover and Assess Your Hadoop Environment
Scan and catalog your Hadoop environment across ETL pipelines, scheduler jobs, downstream applications, and legacy code dependencies. Build a clear inventory of what needs to move before migration begins. This phase helps teams reduce blind spots and improve migration planning accuracy.
Automate Code Translation
Translate SQL, stored procedures, ETL workflows, and other code objects with automation instead of manual redevelopment. SHIFT handles large scale code conversion while accounting for performance and optimization requirements. This phase helps accelerate delivery timelines and reduce migration complexity.
Validate and Prepare for Cutover
Automate data validation and compare results between legacy and cloud environments before production cutover. Verify that migrated workloads perform correctly and that testing is complete before go live. This phase helps teams move to the cloud with greater confidence and fewer post migration issues.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
Latest Snowflake Case Study
Next Pathway helped a UK-based asset management leader migrate from Azure Synapse and Azure Data Factory to Snowflake with zero business disruption and 100% automated code translation.
Read the case study to see how Next Pathway delivered:
Free Step-by-Step Guide
Accelerate your migration to the cloud with SHIFT. Learn how to modernize your legacy data warehouse with 95%+ automation.
What Industry Analysts Say
Rob Enderle
ENDERLE GROUP
Eric Kavanagh
THE BLOOR GROUP
What a structured Hadoop migration covers
A successful Hadoop migration requires a clear plan across four disciplines.
Discovery and dependency mapping
Every code object, ETL pipeline, and data dependency needs to be identified and documented before migration begins. Hidden complexity discovered mid-migration creates delays and risk.
Code translation and modernization
Legacy SQL, Hive scripts, Spark jobs, and ETL pipelines must be converted into optimized cloud-native workloads. Automated translation reduces manual effort and improves consistency.
Validation and functional parity
Every migrated workload must be validated against the legacy source to confirm data accuracy and functional equivalence before cutover. Full parity is critical for success.
Production cutover planning
Cutover requires a defined plan covering resource allocation, rollback decisions, and business sign-off. Teams that prepare early execute migrations faster and with greater confidence.
Latest Insights on Modernization
Five Reasons why Next Pathway is Better than a Box of Consultants for Legacy Data Migration
Time-to-Snowflake: Why Speed Matters More Than Ever In The AI Era
Cloud Migration Resources
Azure Data Migration Checklist
A step-by-step checklist for enterprises to ensure a smooth migration to Azure Synapse.
