Efficiently integrate data from on-premises systems.

With several new features added to Workbench, it’s never been easier to upload data from your on-premises sources.

Workbench partition support. Workbench now supports partition for date fields, which means your data can be divided into date-partitioned sections, making it easy to replace any section quickly with the freshest available data. For data with cure periods, partitioning makes it easy to replace data without using recursive DataFlows.

Enhanced schema protections. Choose when to allow schema changes and on which columns, or block all schema changes completely. These new updates give you confidence and peace of mind that schema changes will only happen when you want them to.

Bulk actions in Workbench. Now you can execute multiple jobs at a time, update credentials for a group of jobs, bulk save jobs in edit mode, export some or all of your jobs from the job list menu, and more.

Take over Connector datasets with Workbench. You can now create a dataset using a connector but then update that dataset with Workbench, so you can switch between different updating tools without having to recreate datasets.

Local Workbench scheduling. You can now schedule jobs to trigger based on the local time of your server or Workbench machine, so you don’t have to adjust for Daylight Savings Time and can be sure when the next job will execute. When the local time on your machine changes, the Workbench job schedule will automatically sync with the time on your machine.

Database-specific plugins. Workbench now reads data types directly from the source system before the data is loaded into Workbench. This eliminates any inconsistency between the data type in your source systems and Workbench, and ensures that the data type will not change after the schema has been set (unless the type changes in the source system). This feature is available for data from MSSQL, MySQL, Oracle, and Postgres.