Creating a river

In Data Integration, a Data Pipeline refers to a River. Rivers are the primary building blocks, with three river types:

• Source to Target Rivers
• Logic Rivers
• Action Rivers

Source to Target rivers

Source to Target Rivers build simple data pipelines that take data from a Source and push it to a Target destination. Data Integration simplifies the process by recognizing the structure of incoming data and creating target tables and columns as needed.

Data Integration supports over 180 Sources and Targets, including Facebook Ads, Google Analytics, Oracle, and popular data warehouses.

Logic rivers

Logic Rivers use a logical data model to define the structure of data elements and the relationships between the Rivers. These rivers handle data transformations and workflow orchestration, and can contain other Rivers.

For data transformations, use SQL for in-warehouse transformations or Python for complex scenarios. Data Integration Orchestration supports branching, multi-step processes, conditional logic, loops, and so on, making it simple to create complex workflows.

Action rivers

Action Rivers connect to any REST API as a data source, custom data ingestion, or data target. For example, an Action River can pull data from a custom API endpoint or push data into a CRM such as HubSpot.

Creating your first river

When you log in for the first time after creating a new Data Integration account, the onboarding process helps you familiarize yourself with the console. Use Create your first data pipeline to create a Source-to-Target River.