Dagster vs dbt Labs 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 dbt Labs
Starts at $10/mo $100/mo
Number of plans 3 4
Free plan
Free trial
Pricing model usage-based per-seat

Solo Plan

$10/mo
  • Pay-as-you-go $0.040/credit
  • 1 User
  • 1 Code location
  • 1 Deployment
  • 30-day free trial

Starter Plan

$100/mo
  • Pay-as-you-go $0.035/credit
  • Up to 3 Users
  • 5 Code locations
  • 1 Deployment
  • Catalog Search
  • 30-day free trial

Pro Plan

Custom
  • Unlimited code locations
  • Unlimited deployments
  • Cost Tracking and Insights
  • Personalized Onboarding Support
  • Private Slack channel
  • Uptime SLAs
  • Custom Security Questionnaires

Developer

$0/mo
  • Browser-based IDE
  • Multi-factor authentication (MFA)
  • Job scheduling
  • Keep on the latest dbt release

Starter

$100/mo
  • dbt Catalog basic
  • dbt Semantic Layer basic
  • dbt Copilot code generation
  • API access

Enterprise

Custom
  • dbt Catalog advanced
  • dbt Semantic Layer advanced
  • dbt Copilot
  • dbt Canvas
  • dbt Insights
  • dbt Mesh

Enterprise+

Custom
  • PrivateLink
  • IP Restrictions
  • Rollback
  • Hybrid projects

Dagster vs dbt Labs FAQ

Which one is cheaper?
Dagster starts lower at $10/mo, compared to $100/mo for dbt Labs.
Can I use either one for free?
dbt Labs has a free plan. Dagster doesn't — though they do offer a free trial.
How do they charge?
Different approach here. Dagster uses usage-based pricing, while dbt Labs goes with per-seat. 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-$100/mo for self-serve tiers, Dagster is undercutting Prefect and positioning against Airflow's operational overhead cost rather than competing on raw price with open-source. They're going after the mid-market data team that wants managed orchestration without paying Astronomer-level enterprise prices. dbt Labs: At $100/seat, they're not cheap — that's squarely mid-to-premium for a data transformation tool, putting them above scrappier open-source-first competitors but below full-stack data platform pricing. They're clearly targeting data-mature teams at growth-stage and enterprise companies, not early-stage shops watching every dollar.

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