Apache Airflow is a workflow orchestration platform to define, schedule, and monitor data pipelines and other batch jobs using Python-defined DAGs.
46.6k stars17.7k forksApache-2.0last commit Actively maintained
5 self-hosted Dagster Cloud alternatives
Managed cloud orchestration platform for building, scheduling, and monitoring data and AI pipelines. Provides asset-aware DAGs, observability and lineage, data quality checks, deployment tooling, and integrations with dbt, Snowflake, Spark and cloud providers.
Alternatives to Dagster Cloud
#2
Declarative, API-first orchestration platform for scheduled and event-driven workflows with a plugin ecosystem, UI editor, CI/CD and Terraform integration.
27.9k stars2.9k forksApache-2.0last commit Actively maintained
#3
Open-source runbook automation platform to schedule jobs, orchestrate workflows, and provide controlled self-service operations via web UI and API.
6.3k stars987 forksApache-2.0last commit Actively maintained
#4
Portable, file-backed workflow orchestrator that defines DAGs in declarative YAML, runs anywhere as a single binary, and includes a modern Web UI for monitoring and control.
3.8k stars317 forksGPL-3.0last commit Actively maintained
#5
On-premises IT task scheduler to centralize, schedule, and run scripts and commands across servers via SSH/WinRM, with workflows, logs, notifications, and an API.
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What replacing Dagster Cloud actually involves
Every option on this page is open source and free to run on your own hardware, so you own the data and there is no subscription to cancel. 4 of 5 shipped a commit in the last six months. Licences in this list: Apache-2.0, GPL-3.0. In exchange you take on hosting, backups and updates yourself.
Browse everything in Automation & Workflow Builders (Low-code).
