Dagster review
A focused orchestration platform for asset-aware data engineering teams.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Dagster is a data orchestration framework and platform for teams building analytics, machine learning, AI, ingestion, transformation, and other production data workflows. Its asset-based model connects data assets with dependencies, lineage, metadata, schedules, sensors, execution history, and quality checks. The open-source core supports local and self-hosted deployments, while Dagster+ provides a managed cloud control plane with serverless or hybrid execution.
Pricing covers several adoption stages. A free plan and a 30-day free trial provide accessible entry points. The Solo plan costs $10 per month and is aimed at personal projects and simple pipelines, with 1 user, 1 code location, and 1 deployment. Starter costs $100 per month for small teams running production pipelines and supports up to 3 users, 5 code locations, 1 deployment, and Catalog Search. Pro adds custom serverless compute, unlimited code locations and deployments, cost tracking and insights, personalized onboarding support, and uptime SLAs, with pricing handled through sales.
Dagster fits organizations that need visibility into how data assets are produced, refreshed, validated, and deployed. Automatic retry configuration, execution logs, timing, run history, asset health dashboards, data quality checks, freshness policies, partitions, and backfills address operational work beyond basic scheduling. Branch deployments and CI/CD workflows support software-oriented delivery, while integrations span dbt, Snowflake, Fivetran, Spark, Databricks, AWS S3, Airbyte, Airflow, Docker, Kubernetes, GitHub, Slack, and OpenAI. Teams seeking a visual workflow builder should consider another option; teams prioritizing lineage, asset health, and data-platform integration are the clearest fit.
Dagster pros and cons
- Where it wins
- Asset lineage, dependencies, partitions, backfills, and freshness policies
- Execution logs, run history, health dashboards, and observability
- Integrations with dbt, Snowflake, Databricks, Spark, and Fivetran
- Where it doesn't
- No visual workflow builder for drag-and-drop pipeline design
- Solo is limited to 1 user, 1 code location, and 1 deployment
- Pro requires contact with sales and adds a less transparent buying step
Dagster fact sheet, pricing and score →
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