Dagster vs Luigi
Dagster
dagster.ioLuigi
github.comSide by side
| Figure | Dagster | Luigi |
|---|---|---|
| Price from | $10/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 6 | 1 |
| Spec score · Data Orchestration Software | 8.2 (#6) | 7.6 (#8) |
| Spec score · Workload Automation Software | 8.3 (#10) | 7.7 (#15) |
| Integrations | The official integration directory lists tools including Airbyte, Anthropic, Apache Airflow, AWS services, and Azure Data Lake Storage. | Documented task types and systems include Hadoop, Hive, Pig, Spark, HDFS, databases, and local files. |
Plans
Dagster
- Solo$10 a month
- Starter$100 a month
- ProPriced on request
- Solo Plan$10 a month
- Starter Plan$100 a month
- Pro PlanPriced on request
In their own words
Dagster
Dagster is a data-aware orchestrator for building, running and monitoring data pipelines and assets. It models assets and dependencies to show lineage across a data platform, while supporting partitions, incremental runs, declarative workflows and fault-tolerant orchestration. An integrated catalog combines data discovery, lineage, workflows and operational metadata. Quality features include code-embedded validation, automated testing, freshness checks and observability tools. The integration directory lists Airbyte, Anthropic, Apache Airflow, AWS services and Azure Data Lake Storage. Dagster+ hybrid deployment keeps compute in a customer’s infrastructure while Dagster manages the control plane. The core framework is open source on GitHub. Platforms listed are API, Linux, self-hosted and web; deployment is hybrid. A 30-day trial is listed. Solo costs $10 a month plus usage charges, and Starter costs $100 a month plus usage charges. Dagster’s website says it is now part of Prefect.
Luigi
Luigi is a free Python package for building and coordinating pipelines of batch jobs. It manages dependencies, workflow execution, visualization, failure handling and command-line integration. The documentation presents it as workflow plumbing for long-running work such as Hadoop jobs, database transfers and machine-learning jobs, including pipelines with thousands of tasks that can take days or weeks. Documented systems include Hadoop, Hive, Pig, Spark, HDFS, databases and local files. A Luigi server provides a web interface for searching and filtering tasks, while its HDFS and local filesystem abstractions support atomic file operations. The project instructs users to install the latest stable version with `pip install luigi`; TOML configuration is available through the optional `luigi[toml]` installation. The repository says Python 3.10 through 3.14 are tested and identifies Apache-2.0 as the license. Luigi is self-hosted, and Spotify's Data Team maintains the project. A mailing list is linked for discussion and questions. Its security policy directs people to report sensitive issues through Spotify's bug bounty program rather than GitHub.