Understanding schedule types and triggers

Scheduling is a crucial part of managing your data workflows. Paradime offers flexible options to ensure your jobs run exactly when you need them and in the most efficient manner. Estimated completion time: 10 minutes

Prerequisites

Access to the Bolt application in Paradime
A Production Connection to your data warehouse (AKA Schedule Connection)
At least one dbt™ model materialized in your dbt™ project

What You’ll Learn

In this guide, you’ll learn about:

Different types of Bolt schedules (Standard, Deferred, and Turbo CI) and when to use them
Various schedule triggers (Scheduled run, On Run Completion, On Merge, Bolt API) and when to use them)
Schedule statuses and their meanings

1. Schedule Types

Paradime supports three main schedule types, each designed for specific use cases:

Type	Description	Best for
Standard	Runs your dbt™ job directly in the production environment	Regular production runs, daily or hourly updates
Deferred	Runs your job in a separate environment before merging changes to production	Testing changes before deploying to production, CI/CD workflows
Turbo CI	Performs rapid, incremental runs of only changed models	Fast feedback on model changes, efficient CI processes

For more details on setting up each type, refer to our advanced scheduling documentation.

2. Schedule Triggers

Paradime supports four main schedule triggers:

Schedule Trigger	What it does	How it works	Best for
Scheduled Run	Runs your job at specific times and frequencies	Uses cron syntax to set the schedule	Regular, time-based job execution (e.g., daily reports, weekly updates)
On Run Completion	Triggers your job after another specified job finishes	You select a “parent” job, and this job will start once the parent completes	Creating dependencies between jobs (e.g., running a summary job after individual data updates)
On Merge	Runs your job when a pull request is merged into a specified branch	Connects to your Git repository and triggers based on merge events.See Defer to Production documentation for details.	Continuous Deployment workflows, ensuring your data pipeline updates with your code changes
Bolt API	Allows you to trigger jobs programmatically from your existing data pipelines	Provides API endpoints to start, stop, or check job statusSee Bolt API documentation for details.	Integrating Paradime jobs with external systems or custom workflows

3. Schedule Statuses

As you manage multiple Bolt schedules, you’ll encounter the following statuses:

Status	Description
✅ Success	The schedule has completed successfully
🚫 Canceled	The schedule was manually canceled or stopped before completion
❌ Error	The schedule encountered an error during execution (AKA the scheduled run “failed”)
⏸️ Paused	The schedule has been temporarily paused
🕐 No runs	The schedule has yet to execute and/or it is not configured to execute.

Related Documentation

Summary

You’ve learned about the different types of Bolt schedules, various trigger methods, and schedule statuses. This knowledge will help you choose the right schedule type and trigger for your specific use cases, and understand the status of your running schedules. Next, we’ll explore how to view run history and analytics for your Bolt schedules, which will help you monitor and optimize your dbt™ workflows.

​What You’ll Learn

​1. Schedule Types

​2. Schedule Triggers

​3. Schedule Statuses

​Summary

What You’ll Learn

1. Schedule Types

2. Schedule Triggers

3. Schedule Statuses

Summary