Cloud Migration from On-Prem and Legacy Systems
Etlworks simplifies the process of migrating data to the cloud. Move data from legacy systems, databases, and files into modern cloud warehouses using flexible and reliable ETL pipelines.
Why it matters: Modernizing your data infrastructure reduces operational costs, improves scalability, and unlocks access to cloud-native tools and analytics.
- Automatic Partitioning
- Change Replication Techniques
- SOC 3 Report (SOC 2 Report available after NDA)
- Security Policies
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Why Etlworks
Supports all sources: Migrate from SQL Server, Oracle, DB2, flat files, APIs, and more.
Destination flexibility: Load data into Snowflake, BigQuery, Redshift, Synapse, and any cloud storage.
Built-in performance optimization: Use automatic partitioning, bulk loading, and incremental updates to maximize speed and reduce cost.
Secure and compliant: On-premise agents, encrypted connections, and audit trails ensure safe data movement.
Proven at scale: Move billions of records with minimal effort using reusable templates and dynamic pipelines.
How Organizations Use Etlworks for Cloud Migration

BioUrja Group, a global leader in energy and agricultural commodities,
turned to Etlworks for their cloud migration needs. By integrating data from multiple
databases and file sources into cloud-based destinations, Etlworks enabled BioUrja to
migrate billions of records from PoC to production in just a few weeks.
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the case study
Community Health Plan of Washington, a nonprofit healthcare provider,
relies on Etlworks to integrate data from SQL Server and Oracle into Azure Synapse. With
high-performance, full-load pipelines and reliable execution, Etlworks plays a central role
in CHPW’s cloud data infrastructure.
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the case study
GEN-I, a global energy trading firm, uses Etlworks to efficiently ETL data
from SQL Server into Snowflake. The platform enables high-volume data movement while
optimizing performance and scalability across many tables.
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the case study

Prymat, a leading European food manufacturer, uses Etlworks to move and
sync large volumes of data from on-prem SQL Server into Google BigQuery. By leveraging
automatic partitioning and reverse ETL, Prymat has streamlined analytics and operational
reporting.
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the case study