Orchestration
One schedule. Every step in order.
Bring source data in, run your models, and send the results where they are needed. Supaflow connects the steps so each one waits for its inputs, with independent work running in parallel.
Keep downstream work in order
Set which steps can start together and which must wait for earlier work.
Include your own logic
Add SQL scripts or Snowflake Python tasks alongside pipelines and dbt Core projects.
Schedule the workflow once
Give the orchestration a schedule instead of timing every step separately.
SQL and Python tasks
Add the code your workflow needs.
Run SQL scripts or Snowflake Python tasks to calculate lead scores or prepare data for the next pipeline. Set dependencies so the code runs after its source data loads and before activation starts.
- SQL tasks on supported datasources
- Python tasks on Snowflake serverless compute
- Explicit dependencies between tasks and pipelines
Scheduling
Schedule the whole workflow.
Schedule the orchestration once and let its dependencies determine the order. Preview upcoming runs and their timezone so your team knows when to expect the next update.
- Daily, weekly, and monthly schedules
- Additional frequencies and cron on eligible plans
- Upcoming run times and timezone
In practice
Keep CRM lead scores current.
Bring source data together, calculate lead scores, and send the results back to Salesforce. Keep the preparation and delivery on the same schedule.
- Independent sources load in parallel.
- The enrichment task waits for the inputs it needs.
- The Salesforce update follows the completed enrichment step.
Python tasks run on Snowflake. SQL tasks run on supported datasources.
Questions before you start
What can I include in one workflow?
Combine ingestion pipelines, dbt Core transformation projects, activation pipelines, SQL scripts, and Snowflake Python tasks. Reuse the pipelines and projects you have already configured.
Can independent steps run in parallel?
Yes. Steps without dependencies can start together. Other steps can wait for specific predecessors or all previous steps, so each part of the workflow follows the inputs you select.
Can I include custom SQL or Python?
Add SQL tasks on supported datasources or Python tasks that run on Snowflake serverless compute. Connect them to the pipelines and dbt projects around them using the same dependency controls.
How often can a workflow run?
Use daily, weekly, or monthly schedules. More frequent runs and custom cron expressions are available on eligible plans. Check upcoming run times and their timezone before saving the schedule.
Can I run a workflow outside its usual schedule?
Yes. Run Now starts an execution without changing the schedule’s next run time. You can also disable and re-enable the schedule without deleting the workflow.
Can I change the workflow as new sources are added?
Edit an existing orchestration to add or remove steps and update dependencies. The dependency graph helps you review which steps run together and which wait for earlier work.
Schedule your next data workflow.
Try Supaflow or walk through your use case with us.
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