Luigi vs Mage

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.

Mage is a web platform for building and operating data workflows. Its listed functions include workflow scheduling, pipeline monitoring, data quality checks, and version control. Integrations cover Stripe, Salesforce, BigQuery, HubSpot, databases, SaaS APIs, cloud storage, files, and streams. Hybrid deployment is available. Mage has a free plan, while Starter costs $29 a month, billed monthly, plus $0.50 per CPU-hour. Starter includes one developer seat, one development environment, and 50 AI credits per month. Team costs $100 a month, billed monthly, plus $0.50 per CPU-hour; it supports up to 10 developer seats, includes one environment, and provides 250 shared AI credits per month. Mage is headquartered in Santa Clara, California, United States.