Databend Cloud has launched Task Flow, a native workflow orchestration feature for building, scheduling, and monitoring multi-step SQL pipelines through a visual drag-and-drop editor. It supports task dependencies, cron or interval scheduling, stream-based CDC triggers, automatic failure suspension, live DAG monitoring, and automatic version snapshots with diff and rollback. Tasks run directly on the Databend warehouse, avoiding external orchestrators and data movement. Use cases highlighted include incremental ingestion, medallion-architecture transformations, scheduled reporting, and data quality checks. The feature is available now, with permissions inherited from Databend Cloud's existing role system.
Table of contents
What Is Task Flow?How Task Flow WorksReal-World Use CasesWhat Makes This DifferentGetting StartedQuestions this post answers
What is Task Flow in Databend Cloud?
Task Flow is Databend Cloud's native workflow orchestration feature that lets you define multi-step SQL workflows as visual graphs, schedule them with cron, interval, or manual triggers, monitor execution through a live color-coded DAG, and roll back to previous versions. Tasks run directly on the Databend warehouse without needing YAML files or external orchestration services. Teams weighing built-in orchestration against external schedulers can track warehouse feature releases like this via daily.dev.
How do stream-based triggers work for CDC pipelines in Databend Cloud Task Flow?
A task can be configured to fire automatically when a stream on a source table has new, unconsumed rows, merging them into a target table without polling or wasted compute. This makes event-driven CDC pipelines as easy to set up as scheduled ones, since stream triggers are treated as first-class citizens rather than an afterthought. Engineers building CDC pipelines can keep up with warehouse-native orchestration features through daily.dev.