Datastage to PySpark Migration Case Study
See how Travinto streamlined ETL workflows with PySpark, delivering superior performance and scalability.
Case Study Overview
Travinto assisted a global retail company in migrating their ETL processes from IBM Datastage to PySpark, enabling a more scalable, distributed computing environment. By leveraging PySpark, we optimized data pipelines, reduced processing time, and scaled effortlessly to handle billions of records.
Project Details
- Client: Global Retail Company
- Tech Stack: Datastage, PySpark, Hadoop, Google Cloud
- Jobs Migrated: 300+ ETL Jobs
- Methodology: Automated Conversion with X2X Converter & Optimized Distributed Processing
Success Metrics
- Time Savings: 80% faster processing times due to distributed computing
- Cost Reduction: 50% cost savings by migrating to an open-source framework
- Scalability: Easily handled billions of records with PySpark's distributed nature
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Read MoreReady to Migrate from Datastage to PySpark?
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