Dagster vs Astronomer Pricing (2026)
How do these two stack up on price? Here's what each one costs, what you get, and where the value sits.
| Dagster | Astronomer | |
|---|---|---|
| Starts at | $10/mo | Custom |
| Number of plans | 3 | 4 |
| Free plan | — | — |
| Free trial | ||
| Pricing model | hybrid | usage-based |
Solo Plan
- Pay-as-you-go $0.040/credit
- Serverless compute $0.010/minute
- 1 User
- 1 Code location
- 1 Deployment
- 30-day free trial
- Asset-based orchestration
- Workflow-based orchestration
- Local development workflow (dg CLI)
- Components
- Declarative Automation
- Partitions and backfills
- Branch deployments
- Virtual assets (Preview)
- Asset checks
- Freshness policies (new API, now GA)
- Integration with dbt tests
- Asset Health status
- Asset metadata in UI
- Asset-level lineage
- Platform and pipeline metrics (30-day lookback)
- Materialization success rate, failure count, step execution time
- Metrics-based alerts
- Dagster skills for Claude Code, Cursor, Codex (open source)
- Dagster+ MCP server (Preview)
- Alerts: email, Slack, Microsoft Teams
- Alert policy types: asset, run, code location, automation, agent downtime
- Serverless deployments
- Hybrid deployments — ECS, Kubernetes, Docker, Azure, local
- Terraform and Pulumi providers
- SOC 2 Type II
- GDPR
- Data portability
- Dagster community
- Support Center and Ask AI
- Billing support
Starter Plan
- Pay-as-you-go $0.035/credit
- Serverless compute $0.010/minute
- Up to 3 Users
- 5 Code locations
- 1 Deployment
- Catalog Search
- 30-day free trial
- Asset-based orchestration
- Workflow-based orchestration
- Local development workflow (dg CLI)
- Components
- Declarative Automation
- Partitions and backfills
- Branch deployments
- Virtual assets (Preview)
- Asset checks
- Freshness policies (new API, now GA)
- Integration with dbt tests
- Asset Health status
- Asset metadata in UI
- Asset-level lineage
- Data Column Lineage
- Catalog search
- Platform and pipeline metrics (30-day lookback)
- Materialization success rate, failure count, step execution time
- Metrics-based alerts
- Dagster skills for Claude Code, Cursor, Codex (open source)
- Dagster+ MCP server (Preview)
- Alerts: email, Slack, Microsoft Teams
- Alert policy types: asset, run, code location, automation, agent downtime
- Role-based access control
- RBAC scope: Per deployment
- Assignable roles: View, Catalog Viewer, Launcher, Editor, Admin
- Serverless deployments
- Hybrid deployments — ECS, Kubernetes, Docker, Azure, local
- Terraform and Pulumi providers
- SOC 2 Type II
- GDPR
- Data portability
- Dagster community
- Support Center and Ask AI
- Billing support
Pro Plan
- Custom Serverless compute
- Unlimited code locations
- Unlimited deployments
- Cost Tracking and Insights
- Personalized Onboarding Support
- Private Slack channel
- Uptime SLAs
- Custom Security Questionnaires
- Asset-based orchestration
- Workflow-based orchestration
- Local development workflow (dg CLI)
- Components
- Declarative Automation
- Partitions and backfills
- Branch deployments
- Virtual assets (Preview)
- Asset checks
- Freshness policies (new API, now GA)
- Integration with dbt tests
- Asset Health status
- Asset metadata in UI
- Asset-level lineage
- Data Column Lineage
- Catalog search
- BI Tool Cataloguing
- Connections (Preview)
- Platform and pipeline metrics (30-day lookback)
- Materialization success rate, failure count, step execution time
- Metrics-based alerts
- Custom metrics from asset metadata
- Cost tracking for BigQuery and Snowflake
- Dagster skills for Claude Code, Cursor, Codex (open source)
- Dagster+ AI chat
- Issues
- AI proactive monitoring and auto implement
- Dagster+ MCP server (Preview)
- Alerts: email, Slack, Microsoft Teams
- Alert policy types: asset, run, code location, automation, agent downtime
- Webhook alerts
- PagerDuty and Datadog
- Alerting asset owners
- Role-based access control
- RBAC scope: Granular roles, per project
- Assignable roles: View, Catalog Viewer, Launcher, Editor, Admin
- SSO
- SAML
- SCIM provisioning — Okta, Entra ID
- Audit logs
- Serverless deployments
- Hybrid deployments — ECS, Kubernetes, Docker, Azure, local
- Terraform and Pulumi providers
- Agent queues — multi-agent routing, multi-region failover
- EU data residency (Dagster+ EU)
- SIEM log export
- SOC 2 Type II
- GDPR
- Data portability
- HIPAA
- Custom security questionnaires
- Dagster community
- Support Center and Ask AI
- Billing support
- Dedicated Slack or Microsoft Teams channel
- Premium support
- Uptime SLAs
Developer
- AI-powered Dag authoring & debugging
- Flexible, scale-to-zero compute
- Hibernating deployments
- API access
- Deployment rollbacks
Team
- End-to-end observability & data quality
- Network isolation with Dedicated clusters
- High availability deployments
- Audit logging (7-day retention)
- 24x5 support availability
Business
- SSO enforcement
- CI/CD enforcement
- Audit logging (90-day retention)
- 24x7 support availability (1 hour SLA)
Enterprise
- Remote execution agents
- Cross-region Disaster Recovery (add-on)
- Custom RBAC
- SCIM provisioning
- IP access list
- Organization dashboards
Dagster vs Astronomer FAQ
- Which one is cheaper?
- One or both use custom pricing, so it depends on your specific needs.
- Can I use either one for free?
- Neither has a free plan. But Dagster and Astronomer offer a free trial.
- How do they charge?
- Different approach here. Dagster uses hybrid pricing, while Astronomer goes with usage-based. That changes the math depending on your team size and usage.
- Which one is a better deal?
- Depends on what you need. Dagster: At $10 and $100 entry points, Dagster undercuts most orchestration and data platform competitors that charge per-seat or start pricing conversations well north of $500/mo. They're clearly fishing for indie developers and small data teams who'll self-serve now and hopefully graduate into Pro as pipelines multiply. Astronomer: Astronomer sits in the premium band of the managed-Airflow space — this isn't a scrappy open-source wrapper, it's the commercial layer for teams already committed to Airflow at scale. They're not competing on sticker price; they're competing for enterprises that want a vendor to own the operational headache of running Airflow reliably.
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