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SPECIFICTION
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Dagster vs Luigi

Dagster

dagster.io

Luigi

github.com

Side by side

FigureDagsterLuigi
Price from$10/moFree
Free plan—Yes
Free trialYes—
Open source——
WebYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published61
Spec score · Data Orchestration Software8.2 (#6)7.6 (#8)
Spec score · Workload Automation Software8.3 (#10)7.7 (#15)
IntegrationsThe 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

Dagster pricing →

Luigi

  • LuigiFree

Luigi pricing →

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.

Visit dagster.io

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.

Visit github.com