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Orchestrate your data pipelines with confidence

Dagster is a cloud-native orchestrator for building, testing, and monitoring data assets throughout the entire development lifecycle.

Get startedAPI reference

Quick start

Get up and running with Dagster in minutes

1

Install Dagster

Install Dagster using pip or uv:
pip install dagster dagster-webserver
Or with uv:
uv add dagster dagster-webserver
2

Define your first asset

Create a Python file with a simple data asset:
my_data_pipeline.py
import dagster as dg
import pandas as pd

@dg.asset
def my_dataset() -> pd.DataFrame:
    return pd.DataFrame({
        "id": [1, 2, 3],
        "name": ["Alice", "Bob", "Charlie"]
    })
Assets are the core building blocks of Dagster. Each asset represents a data object that you want to build and maintain.
3

Create a Definitions object

Define your code location by wrapping assets in a Definitions object:
my_data_pipeline.py
import dagster as dg
import pandas as pd

@dg.asset
def my_dataset() -> pd.DataFrame:
    return pd.DataFrame({
        "id": [1, 2, 3],
        "name": ["Alice", "Bob", "Charlie"]
    })

defs = dg.Definitions(
    assets=[my_dataset]
)
4

Launch the Dagster UI

Start the Dagster web server to visualize and execute your pipeline:
dagster dev -f my_data_pipeline.py
Navigate to http://localhost:3000 to see your asset graph and materialize your assets.
The Dagster UI provides a visual interface for exploring your data lineage, monitoring runs, and debugging issues.

Explore by topic

Learn about Dagster’s core capabilities

Assets

Define data assets with Python functions and dependencies

Jobs & Ops

Build task-based workflows and graphs

Resources

Configure external services and shared dependencies

Schedules

Automate pipeline execution on a schedule

Partitions

Process data in time windows or logical partitions

Testing

Test your data pipelines with confidence

Integrations

Connect with your existing data stack

dbt

Orchestrate dbt models as Dagster assets

Airflow

Migrate from Airflow or run both side-by-side

AWS

Deploy on AWS with S3, ECS, and more

Databricks

Run Spark jobs on Databricks clusters

Snowflake

Manage Snowflake tables and queries

View all

Explore 100+ integrations

Ready to build your data platform?

Start building production-ready data pipelines with integrated lineage, observability, and testing.

Get started with Dagster