Etlworks works with almost all known relational databases.
What can you do with databases in Etlworks
ETL transformation where the source is a relational database |
ETL transformation where the destination is a relational database |
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Change replication using a high watermark | ||
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Videos
ETL and CDC with databases
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ETL multiple tables by wildcard
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Related case studies
ETL data from multiple SQL Server tables into Snowflake using wildcard-based workflows, parallel partition processing, and high-watermark incremental loads.
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GEN-I, a global leader in energy trading, needed a powerful data integration solution to efficiently ETL data from their SQL Server databases into Snowflake. The company sought a platform that could handle high-volume data with speed and accuracy while leveraging advanced ETL techniques to optimize performance and scalability across multiple tables. |
Community Health Plan of Washington case study ETL and CDC data from SQL Server and Oracle databases to Azure Synapse.
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Community Health Plan of Washington (CHPW), a nonprofit providing health coverage for Washington residents, leverages Etlworks to efficiently ETL data from SQL Server and Oracle databases into their Azure Synapse data warehouse. Etlworks’ ability to handle frequent full database reloads with exceptional performance and reliability makes it a cornerstone of CHPW’s data integration strategy. |
Stream CDC data from 1,500 MySQL databases into Snowflake in real-time. |
Intertek Alchemy, a global leader in workforce training solutions, faced a monumental challenge: seamlessly streaming real-time Change Data Capture (CDC) events from over 1,500 MySQL databases into Snowflake. Despite exploring multiple data integration platforms, no solution on the market could meet their scalability and real-time performance requirements—until they discovered Etlworks. |
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