What Dagster is
Dagster is an orchestration platform for data and AI pipelines. The site describes a unified control plane covering data orchestration, observability, catalog and lineage, and also mentions an AI analyst for Slack.
It supports ETL and ELT, dbt, Databricks, Python transformations and AI or ML workflows.
What you can do with it
- Orchestrate data and AI pipelines
- See asset lineage and a catalog
- Monitor runs and failures
- Coordinate work across a data team
Who it is for
- Data engineering teams
- ML platform teams
- Analytics engineering teams
What to watch out for
- It orchestrates and monitors; it does not design your data model or business logic
- Reliability depends on task design, data quality and team governance
- It suits teams with continuous pipelines more than one-off scripts
- Self-hosting brings operational responsibility
Pros & cons
✓ What we like
- Data and AI workflows in one control plane
- Lineage and catalog built in
- Observability for pipelines
! What to watch out for
- Not a data modelling tool
- Requires established data processes
- Operational overhead when self-hosted
FAQ
Is it a scheduler or an AI platform?
Both, but the positioning is a unified control plane for data orchestration, AI workflows and observability.
What team size fits it?
Engineering teams with continuous data processes, collaboration and production needs.
Does it solve data quality?
No. It orchestrates and monitors; task logic and governance remain yours.
Last reviewed: 2026-09-17
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