Task Factory 2018.3 Delivers Support for Azure Data Factory and Cloud Data

Task Factory 2018.3 extends the toolbox for SQL Server Integration Services (SSIS) by providing high-performance SSIS components that now connect to Amazon S3, Microsoft Azure storage accounts, and Azure Data Factory (ADF). Rather than having to write custom code, you can save time with Task Factory components and tasks.

Let’s take a closer look at some of these new connectivity features, which address specific business scenarios as well as data warehousing and other back-end operations.

Task Factory 2018.3 includes Amazon S3 connectivity so that you can pull information out of or push information to Amazon S3 using SSIS. This release also provides the same functionality for Microsoft Azure Storage.

Support for running SSIS packages in ADF is relatively new; Microsoft introduced SSIS support in ADF as a preview at the end of 2017 and released it to production this year. ADF is a cloud-based data integration tool. SSIS has always been an on-premises data integration pool. This new support allows you to lift and shift your SSIS packages to run in the cloud on ADF.

Task Factory now supports installation and setup in the ADF SSIS Integration Runtime (IR). The same SSIS packages that you're currently running on-premises that use Task Factory can run in ADF—no package modifications are required. This support enables you to move SSIS processes to the cloud without giving up the enhancements to SSIS that Task Factory offers.

There are some steps you need to take when you are setting up your ADF cluster to ensure Task Factory is available and can run properly. For instructions on how to create an Azure SSIS IR and install Task Factory during the startup process of the IR, please visit sentryone.com/products/task-factory/feature/azure-data-factory-edition-ssis/install-activate.

To learn more about deploying SSIS packages with Task Factory to Azure Data Factory, check out our on-demand webinar "SSIS in the Cloud: How to Read and Write to the Cloud with Task Factory to Azure Data Factory."