Apache Airflow vs Dagster
No clear leader: Dagster (70.0) and Apache Airflow (69.0) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Apache Airflow
Apache Airflow is a workflow orchestration platform that enables users to define data pipelines in Python and schedule their execution across distributed workers. It provides a web interface for visualization and monitoring, plus extensive integrations with cloud platforms and services.
Dagster
An orchestration and observability platform that models data assets, manages their dependencies, and integrates lineage tracking, quality monitoring, and data cataloging for managing pipelines from development to production.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Dagster
From $10/month. Free 30-day trial. Subscription plus metered usage model.
- Solo$10/month + $0.04/credit + $0.01/minute serverless compute
- Core and asset-based orchestration
- Local development (dg CLI)
- Partitions and backfills
- Branch deployments
- Asset checks
- +3 more
- Starter$100/month + $0.035/credit
- All Solo features
- Workflow-based orchestration
- Freshness policies
- Data column lineage
- BI tool integration
- +5 more
- ProContact sales
- All Starter features
- Custom serverless compute
- Cost tracking and insights
- Personalized onboarding support
- Private Slack channel
- +8 more
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- Databricks
- Snowflake
- dbt Cloud
- Slack
- Salesforce
- Tableau
- Datadog
- ClickHouse
- Airbyte
- PagerDuty
Apache Airflow
- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
- PostgreSQL
- MySQL
- MongoDB
- Redis
- Kubernetes
- Docker
- Apache Spark
- Apache Kafka
- Apache Cassandra
- Apache Flink
- Apache Druid
- Elasticsearch
- Jenkins
- GitHub
- OpenAI
- Anthropic
- Cohere
- Pinecone
- Weaviate
- Qdrant
- Oracle
- +27 more
Dagster
- dbt
- Spark
- Azure
- AWS
- Soda
- Microsoft Teams
- Python
- Fivetran
- AWS S3
- AWS Redshift
- AWS EMR
- AWS Glue
- AWS Athena
- AWS CloudWatch
- Looker
- Power BI
- Sigma
- Ray
- lakeFS
- OpenMetadata
- Cube
- SFTP
- Microsoft SharePoint
- Slurm
- +5 more
Apache Airflow or Dagster: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.