Modernize legacy ETL workloads on Talend/Informatica/Datastage, etc., by converting them into production‑ready PySpark pipelines on AWS Glue, reducing ETL licensing, infrastructure overhead, and long‑term operating costs through automation‑led migration.
Why Move from
Legacy ETL to Modern ETL Tools?
As organizations scale analytics, AI, and cloud initiatives, legacy ETL architectures often struggle to support modern data platform requirements. Systems designed for earlier operating models introduce operational complexity, rising infrastructure costs, and performance limitations when applied to cloud-scale data environments.
Rising Infrastructure & Licensing Costs
Legacy ETL platforms often rely on dedicated infrastructure and licensing models that steadily increase operational costs as data workloads grow.
Key challenges
- Rising ETL licensing costs
- Dedicated servers for ETL runs
- High infrastructure overhead
Operational Complexity Across ETL Environments
Traditional ETL systems frequently depend on fragmented tooling for scheduling, orchestration, and monitoring, creating operational silos.
Key challenges
- Fragmented ETL tool ecosystem
- Complex job orchestration flows
- Siloed data and cloud teams
Performance Limits for Modern Data Workloads
As data volumes increase and organizations adopt cloud data platforms, legacy ETL pipelines can introduce scalability and performance bottlenecks.
Key challenges
- Long-running batch pipelines
- Data pipeline scaling limits
- Slower analytics innovation
From Legacy ETL to Cloud Pipelines
AWS Glue and PySpark
AWS Glue provides a serverless, Spark‑based ETL platform designed for cloud‑native data processing. Migrating Legacy pipelines like Talend to PySpark on AWS Glue shifts ETL from infrastructure management to scalable, code‑driven data engineering aligned with AWS data architectures. This transition establishes a cleaner, more flexible foundation for the cost, scalability, and automation benefits explored in the next sections.
Manual Migration Vs Automated ETL Modernization
Cloud‑native platforms shift ETL economics from fixed licensing and infrastructure ownership to usage‑based compute. Migration approaches that rely on manual rewrites often struggle to achieve ETL cost optimization.
Capability
Automated ETL Modernization
Manual Migration
Automated job analysis & reports
✅
❌
Auto-converted PySpark Glue jobs
✅
❌
Prebuilt Glue job templates
✅
❌
Small team handles more jobs
✅
❌
Standardized patterns, lower risk
✅
❌
Cost
Low
High
Accelerate ETL Migration
with EZConvertETL
Modernizing legacy ETL environments often leads to dual costs, operational delays
and re-write complexity. But you can adopt parallel migration frameworks with EZConvertETL.
How EZConvertETL Automates
Talend‑to‑PySpark on AWS Glue
EZConvertETL is Wavicle’s automated ETL migration accelerator that streamlines Talend‑to‑PySpark conversion on AWS Glue, reducing migration effort by 80–90% through intelligent job analysis, code generation, and built‑in validation.
From cloud migration to advanced data analytics, Wavicle ensures seamless integration with AWS-native tools, optimizing workflows for performance and cost efficiency. Equipped with certified AWS professionals, Wavicle empowers organizations to modernize their data infrastructure, improve agility, and drive innovation in the cloud.
A Structured, Automated 4‑Step Migration Framework
EZConvertETL enables modernization without forcing disruptive rewrites or architectural resets.
1. Automated Job Analysis
Scans Talend repositories to inventory jobs, components, dependencies, and complexity, producing clear Excel reports.
2. Intelligent ETL Conversion
Parses Talend logic (mappings, transformations, routines) and auto‑generates equivalent, optimized PySpark code aligned to AWS Glue.
3. Rigorous Unit Testing
Validates each auto‑converted Glue job against original Talend outputs, quickly flagging mismatches to ensure accuracy and consistency.
4. Production‑Ready Delivery
Fully tested AWS Glue PySpark jobs with test reports and deployment guidance for S3, orchestration, and database integrations.
Our ETL Migration Process
Wavicle delivers a proven, low‑risk ETL migration process for enterprises moving from Talend to PySpark on AWS Glue. Our structured Talend migration strategy minimizes disruption while maximizing automation through EZConvertETL.
Designed to support phased modernization, parallel run, and enterprise change‑management requirements.
1. Free Migration Assessment
Automated scan of Talend repositories with job inventory, dependency mapping, complexity scoring, and timeline estimates.
2. Fixed‑Scope Cost Proposal
Clear migration cost model, ROI forecast, and a fixed-scope delivery plan -so you know exactly what to expect before committing.
3. EZConvertETL Automation
80–90% automated conversion of Talend logic into production‑ready AWS Glue PySpark jobs.
4. Zero‑Data‑Drift Validation
Automated testing confirms every converted job matches original Talend outputs, with detailed validation reports.
5. Production Cutover
Seamless deployment of Glue jobs with orchestration, monitoring setup, and team enablement for cloud‑native ETL operations.
ETL Modernization with EZConvertETL – What You Get?
Wavicle’s approach enables teams to modernize their data platforms while maintaining operational continuity, validating migration outcomes, and preparing their data infrastructure for advanced analytics and AI-driven workloads.
Testomonial
Trusted by
Enterprise Leaders
Wavicle is a trusted AWS data modernization partner and recognized leader in AWS Glue migrations, helping Fortune 500 organizations modernize legacy ETL to cloud-native PySpark on AWS.
100+
AWS Certifications
48,000+
ETL jobs analyzed
$1M+
Cloud Cost Savings in 90 Days
80%
Automated Conversion Using EZConvertETL
Unlock 80% Faster Talend Migration
Schedule your Talend migration consultation to see how EZConvertETL delivers AWS Glue PySpark jobs in weeks, not months, with detailed ROI modeling.
Frequently Asked Questions
Queries You Might Want To Ask
Helpful answers to your questions about our Accelarator
How long does a Talend → AWS Glue migration take?
Timelines vary significantly based on estate size and architectural complexity. Manual migration approaches often extend modernization programs, while automation‑led frameworks compress delivery timelines.
Do I need to manually rewrite Talend jobs for AWS Glue?
No. EZConvertETL automates 80–90% of Talend‑to‑PySpark conversion.
What cost savings can I expect?
You can expect up to 50% lower migration cost and up to 75% savings by eliminating Talend licensing and moving to serverless AWS Glue.
Is PySpark mandatory for AWS Glue ETL jobs?
Yes. AWS Glue natively runs ETL on PySpark; EZConvertETL generates Glue‑optimized PySpark code automatically.
Can Talend and AWS Glue run in parallel during cutover?
Yes. We support parallel pipelines and phased cutover for zero downtime.
What happens to custom Java code in Talend jobs?
EZConvertETL converts most Java routines automatically; complex custom logic is flagged for rapid PySpark refactoring.
How do you ensure data accuracy after migration?
Every converted Glue job is validated against Talend outputs using automated parity tests and detailed validation reports.
Is the initial migration assessment free?
Yes. The automated assessment scans your Talend repository and generates job inventory, complexity scoring, and timelines within days.
Do you support hybrid Talend + AWS Glue environments?
Yes. However, full migration to AWS Glue unlocks serverless scaling, operational simplicity, and long‑term cost optimization.
How does EZConvertETL handle Talend job dependencies?
The Analyzer automatically maps dependencies, extracts contexts, and converts them into Glue parameters and Workflows.