What is Dagster?
Dagster is an open-source data orchestrator that models pipelines as software-defined assets rather than just tasks, aiming for easier testing, observability, and data-aware scheduling than plain task-based orchestrators. In 2026, Prefect announced it was acquiring Dagster Labs (formerly Elementl) - the company, codebase, customers, and team - with the deal expected to close in August 2026. The open-source Dagster project continues under its existing license, and Dagster+ (the managed cloud offering) continues with no changes to existing deployments, contracts, or support.
Read the full overview
Sources checked 27 September 2026: official website, pricing page, documentation, GitHub.
Key capabilities
- Open-source core: Free, self-hostable orchestrator with software-defined assets and a local dev UI.
- Dagster+: Managed cloud service from $10/month (Solo) with pay-as-you-go credits, up to Enterprise contact-sales tiers.
- Continuity commitment: Existing Dagster+ customers keep current pricing, support, and no forced migration following the Prefect acquisition.
Core areas are asset-based pipeline orchestration, data lineage/observability, and local testing of pipelines before deployment.
Shortlist Dagster if you want an asset-centric orchestrator with strong local testing and lineage. Its recent acquisition by Prefect doesn't change the open-source license or existing Dagster+ contracts, but it's worth asking about the long-term product roadmap under the combined company.
Given the pending integration with Prefect, ask directly about the post-acquisition roadmap and long-term support commitments before standardizing on Dagster+ for critical infrastructure.
Technical details
- Access
- Self-hosted
- Source model
- Open source
- Founded
- 2018
- Headquarters
- San Francisco, USA
- Pricing model
- Open source
- API
- Available
- Published release
- Dagster 1.13.24 ↗ (checked )
- Source check
- Primary source ↗ checked
- Website
- dagster.io ↗
Official resources
What to verify for your environment
Start from the users, systems and operating responsibilities the tool needs to support.
- Confirm current features, licensing and support terms with the publisher.
- Validate deployment, data location, access control, backup and recovery requirements.
- Test integrations, export paths and a representative operational workflow before committing.
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