Low Code Data Integration

Build complex workflows and event-driven scenarios with no or minimal coding. Use a graphical user interface to create, test and schedule data integration flows in minutes. Track changes using built-in version control.

Low code data integration

Do More Faster and Smarter

Etlworks helps data engineers tackle their most complex challenges with minimum effort and maximum efficiency. Almost everything from creating connections to bulding and testing complex data pipelines can be performed using graphical user interface. A single mouse click allows developer to configure a flow to resume from the last step. Data sourses can be processed by a wildcard which saves hundreds of hours when developing flows. Never lose a change with built-in version control.

How To	Documentation	Why do you need it
Technique Use Etlworks UI Use Etlworks graphical user interface to create, test, schedule and monitor connections and data integration flows.	Documentation Using Etlworks	Why do you need it To create, test, schedule and monitor connections and data integration flows To manage users and tenants To manage your Etlworks account To personalize the development environment To monitor the health of the Etlworks instance
How To Use Explorer Etlworks Explorer helps you see and understand your data. Whether it’s in a spreadsheet, an SQL database, a file, or a web service, you can connect and visualize any data anywhere.	Documentation Using Explorer	Why do you need it To explore data sources and their structure, regardless of the format or location. Use it to develop and debug data integration flows To see data in a grid and raw (original) format. Discover dependencies by drilling down into the nested datasets, quickly filter out and sort data To use SQL to query data in any format, including databases, web services, structured and flat files. Leverage your natural ability to spot visual patterns quickly. Share queries with a team
How To Use built-in version control Etlworks automatically tracks changes for all design artifacts: Connections, Formats, Listeners, Flows, Macros, and Schedules. There is nothing to configure except the retention policy.	Documentation Using version control	Why do you need it To view the history of changes or who-changed-what-and-when To compare any two versions To revert to any previous version To add comments to the commit when saving the artifacts
How To Export and import design artifacts In Etlworks, you can import a whole Flow (or multiple Flows) with all its Connections and Formats, then export it to any tenant or environment.	Documentation Export and Import Flows Collision policies Duplicate flows Export and Import Connections and Formats	Why do you need it To copy flows, connections and formats to different environments and tenants To duplicate flows, connections and formats
How To Configure flow to resume from last step It is possible to configure the ETL Flow which has multiple source-to-destination transformations or a single transformation configured with a wildcard source to retry failed or not yet executed steps (transformations) on restart.	Documentation How to retry only failed or not yet executed steps	Why do you need it To save time when executing flows. A Flow configured to retry failed or not yet executed steps on restart (manually or by the scheduler) will skip the successfully executed, retry failed, and execute not yet executed steps
How To Process data by wildcard In Etlworks it is possible to process data sources (such as database tables) and files by a wildcard.	Documentation Process files in a folder by a wildcard filename Copy data from tables matching a wildcard name from one schema or database to another File operations using wildcard	Why do you need it To save time and effort. Instead of configuring multiple source-to-destination transformations (which can be hundreds or even thousands), you can create a single transformation using wildcard patterns for the source and destination
How To Build complex pipelines In Etlworks there is an easy way to combine multiple Flows into a single nested Flow (pipeline), add conditions, loops, and parallel execution.	Documentation Complex workflow (nested Flow)	Why do you need it Using this technique, you can create very complex data integration pipelines, where one Flow is used as input for another, where Flow is executed multiple times based on conditions, or where Flow is not executed at all when conditions are not met

Low Code Data Integration

Do More Faster and Smarter

Use Etlworks UI

Use Explorer

Use built-in version control

Export and import design artifacts

Configure flow to resume from last step

Process data by wildcard

Build complex pipelines

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