Getting Started with Declarative Orchestration
See how Kestra can simplify your data pipelines—and scale beyond them.
Book a demoKestra vs. Dagster: Orchestrate Your Business, Not Just Your Pipelines
Dagster builds data pipelines for Python teams. Kestra automates business workflows. One optimizes your data team. The other transforms how your company operates.
Two Platforms, Two Philosophies
Universal Orchestration: Pipelines & Workflows
Universal orchestration platform built on declarative YAML and an API-first architecture. Orchestrate data pipelines, ETL jobs, and complex workflows in any language without forcing your team into a single framework.
"How do I get pipelines running without learning a framework first?"
Pipeline Orchestration
Data orchestration platform built around Software-Defined Assets. Model data pipelines as a graph of assets, emphasizes the asset abstraction and Python-native development.
"How do I manage data pipelines in Python?"
Pipelines Optimize Data Teams.
Workflows Transform a Business.
Business-critical Workflows
- Automate how your company operates
- Cross-functional: data + ops + business
- Revenue and competitive advantage
- Strategic business transformation
- Serves the entire organization
Data Pipelines
- Move data from A → B → C
- Data engineering scope
- Efficiency gains
- Cost center optimization
- Serves the data team
Time to First Workflow
Dagster requires restructuring your logic into Software-Defined Assets with @asset decorators, IOManagers, and repository definitions. Kestra takes a simpler approach: define orchestration in declarative YAML, write business logic in whatever language fits the task.
~5
Minutes
curl -o docker-compose.yml \https://raw.githubusercontent.com/kestra-io/kestra/develop/docker-compose.ymldocker compose up
# Open localhost:8080# Pick a Blueprint, run it. Done.Download the Docker Compose file, spin it up, and you're ready—database and config included. Open the UI, pick a Blueprint, run it. No Python environment to wrestle with.
~30
Minutes
pip install dagster dagster-webserverdagster dev
# Now restructure your code...Requires Python environment setup, understanding of assets/definitions structure, and refactoring your code into Dagster's Assets.
Workflows Your Whole Team Can Read
Kestra: Readable by your whole team
YAML is readable on day 1. Our docs are embedded in the UI for easy reference, the AI Copilot writes workflows for you, or start with our library of Blueprints. No special training required.
Dagster: Requires the Python developer lens
Requires Python environment setup, understanding of assets/definitions structure, and refactoring your code into Dagster's Assets.
One Platform for Your Entire Technology Stack
Orchestrate across data pipelines, infrastructure operations, business processes, and customer workflows in one unified platform. Event-driven at its core.
Purpose-built for data engineering. Excellent at orchestrating tables, models, and reports. Not designed for infrastructure or business automation.
Kestra vs Dagster at a Glance
| | | |
|---|---|---|
| Primary use case | Universal workflow orchestration | Data pipeline orchestration |
| Workflow definition | Declarative YAML | Python code |
| Script execution | Run scripts directly | Requires @asset decorators and IOManagers |
| Languages supported | Agnostic (Python, R, Bash, Node.js, SQL & more) | Python (others via subprocess) |
| Users | Engineers, analysts, ops, business users | Data engineers |
| Self-service for non-engineers | Kestra Apps | Not designed for this |
| Infrastructure automation | Native support | Not designed for this |
| Business process automation | Native support | Not designed for this |
“Kestra made the data mesh possible. We produce far more data now, and deliver it nearly 10 times faster.”
Julien Henrion, CDO @ Leroy Merlin-900%
In Data Production
+250
Active Users
+5000
Workflows Created
How much risk and cost are you still accepting today?
Read the storyKestra Is Built for How Data Teams Actually Work
Bring your own scripts
Bring your existing Python, SQL, Shell, and R scripts. Define workflows in declarative YAML. No wrappers, no decorators, no refactoring required—just orchestrate.
Minutes to first workflow
Build your first scheduled workflow in under 5 minutes with our Quickstart Guide. No Python environment, no asset restructuring, no IOManagers to configure. Write YAML and execute.
Orchestrate anything
From data pipelines to infrastructure provisioning, Kestra handles it all in one platform.
The Right Tool for the Right Job
Choose Kestra When
- You're automating business workflows, not just data pipelines.
- Your team works across languages—Python, SQL, Bash, R. You need orchestration that doesn't force everyone into Python.
- You want a workflow running today. No framework to learn, no paradigm shift required.
- Non-engineers need to participate. Business users trigger and monitor workflows without writing code.
Choose Dagster When
- Your focus is data pipelines in Python and that's all you need.
- Your team is Python-native and don't need other languages.
- You're willing to invest in learning SDAs for lineage and data-aware scheduling.
- Your users are data engineers. You don't need self-service for non-technical teams.
Frequently asked questions
Find answers to your questions right here, and don't hesitate to Contact us if you couldn't find what you're looking for.
