Apache Airflow vs Dagster: Which is Better in 2026?
Apache Airflow and Dagster are both Data Orchestration tools, made for different people. Apache Airflow is for data teams that want a vendor-neutral orchestrator with a large integration ecosystem, self-hosted or rented from a managed provider. Dagster is for data engineers who want pipelines described as the tables and models they produce, with lineage built in.
Quick verdict
There’s no single winner; pick on your constraint. Choose Apache Airflow if you want the orchestrator most data engineers have already used. Choose Dagster if you want lineage and freshness tracked without extra tools.
Apache Airflow vs Dagster: Side by Side
| Apache Airflow | Dagster | |
|---|---|---|
| Category | Data Orchestration | Data Orchestration |
| What it is | Open-source workflow orchestrator | Asset-based data orchestrator |
| Workflows written in | Python (other languages from 3.4) | Python |
| Licence | Apache 2.0 | Apache 2.0 |
| Managed option | Third-party: Astronomer, MWAA, Cloud Composer | Dagster+ from $10 a month |
| Free access | Free | Open source; 30-day Dagster+ trial |
| Pricing | Free | Free · paid from $10/mo |
| Starting price | Free tier available | Free tier available |
| Free tier | ||
| Rating | 4.5 | 4.6 |
| Best for | Data Orchestration: open source, Python DAGs, integrations | Data Orchestration: data assets, lineage, Python |
Ratings are App Stack Builder’s editorial score out of 5, not an average of user reviews.
Pros & Cons
- Free and vendor-neutral
- Huge integration catalogue
- Easy to hire for
- Managed versions on every big cloud
- Running the scheduler and workers yourself is real work
- Task-centric rather than data-asset-centric
- Local development is heavier than newer tools
- Lineage and freshness from the asset model
- Pleasant local development
- Cheap managed entry point
- Apache 2.0 core
- Credit billing needs watching
- Asset model is a shift from task DAGs
- Smaller hiring pool than Airflow
Key Features Compared
Apache Airflow
- Apache Software Foundation project, free to run
- Workflows (DAGs) written in Python, with a web UI to monitor and rerun tasks
- Airflow 3.4.0 (November 2026) adds task loops, DAGs in any language and AI agent tasks
- Provider packages for the major clouds and data tools
- Managed hosting from Astronomer, Amazon MWAA or Google Cloud Composer
Dagster
- Open source under Apache 2.0
- Dagster+ Solo: $10 a month, 1 user, 1 code location, $0.040 per credit
- Dagster+ Starter: $100 a month, up to 3 users, 5 code locations, $0.035 per credit
- Pro: custom, unlimited code locations and deployments
- Serverless compute $0.010 a minute on Solo and Starter; 30-day trial
Choose Apache Airflow if…
- You want the orchestrator most data engineers have already used.
- You need ready-made operators for many cloud services.
- You want to switch between self-hosted and managed without rewriting DAGs.
Choose Dagster if…
- You want lineage and freshness tracked without extra tools.
- You care about testing pipelines locally before deploying.
- You want a cheap managed plan for a solo data engineer.
Frequently Asked Questions
Is Apache Airflow better than Dagster?⌄
There’s no single winner; pick on your constraint. Choose Apache Airflow if you want the orchestrator most data engineers have already used. Choose Dagster if you want lineage and freshness tracked without extra tools.
What is the difference between Apache Airflow and Dagster?⌄
What it is. Apache Airflow: Open-source workflow orchestrator. Dagster: Asset-based data orchestrator. Workflows written in. Apache Airflow: Python (other languages from 3.4). Dagster: Python. Managed option. Apache Airflow: Third-party: Astronomer, MWAA, Cloud Composer. Dagster: Dagster+ from $10 a month. Free access. Apache Airflow: Free. Dagster: Open source; 30-day Dagster+ trial.
Apache Airflow vs Dagster: which is cheaper?⌄
Apache Airflow pricing: Free. Dagster pricing: Free · paid from $10/mo. Confirm current pricing on each tool's official site, as plans change.
Which is rated higher, Apache Airflow or Dagster?⌄
On our editorial score, Apache Airflow is 4.5 out of 5 and Dagster is 4.6 out of 5, so Dagster is slightly ahead. This is our own score, not an average of user reviews.
When should I skip both Apache Airflow and Dagster?⌄
Skip Apache Airflow if you think in tables and models rather than tasks. Dagster’s asset model fits that. Skip Dagster if you need the widest operator library and hiring pool. Apache Airflow has it.
Sources · tool facts checked November 2026
See more options in our guide to the best data orchestration tools for startups.
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