Case Study: GEN-I achieves faster SQL Server to Snowflake integration with Etlworks

GEN-I speeds SQL Server to Snowflake integration with Etlworks using parallel partition processing

gen-i, a global leader in energy trading, faced challenges in efficiently ETLing high-volume data from their SQL Server databases into Snowflake. They needed a solution for incremental loads, processing multiple tables via wildcard workflows, and performance optimization through parallel processing. They chose the Etlworks data integration platform to address these specific needs.

The solution implemented by Etlworks utilized wildcard-based workflows and parallel partition processing to extract data. This was combined with incremental load via high-watermark replication and optimized batch loading into Snowflake. The results included streamlined management, significantly improved performance, optimized resource usage, and seamless integration, enabling gen-i to handle increasing data volumes efficiently.

Gen-I