Dagster and Prefect are both open-source-rooted workflow orchestration platforms, and per both companies' own FAQs, Prefect acquired Dagster Labs in July 2026…
Best for Dagster: Teams that want asset-lineage-first orchestration with native dbt, Snowflake, and Fivetran hooks, branch deployments for testing pipeline changes, and AI-assisted pipeline diagnostics, and who are prepared to pay from day one (Dagster+ has no permanent free tier).
Best for Prefect: Teams that want to start free on the Hobby plan and add orchestration to existing Python code via a decorator rather than restructuring pipelines around assets, and who value a large open-source community (40,000+ GitHub stars).
At a Glance
Dagster
Prefect
Primary category
Automation
Automation
Rating
Not documented
Not documented
Pricing model
Freemium / Open Source
Freemium
Starting price
Free (self-hosted); Dagster+ from $120/month
Free (open source or Hobby cloud tier); paid plans from $100/month (Starter)
Free plan
Not documented
Yes
Free trial
Yes
Yes
Platforms
Web
Not documented
Team collaboration
Not documented
Not documented
AI features
Yes
Not documented
Public API
Yes
Yes
Key Differences
Corporate relationship
Dagster: Dagster's own FAQ confirms Prefect acquired Dagster Labs in July 2026.
Prefect: Prefect's FAQ states the same acquisition — Prefect acquired Dagster Labs in July 2026.
Common ownership can affect long-term product direction, support priorities, and potential convergence of the two platforms.
Free tier for the hosted product
Dagster: Dagster+ has no permanent free tier — only a 30-day free trial on the Solo ($120/month) and Starter ($1,200/month) plans.
Prefect: Prefect Cloud offers a free Hobby plan ($0) with 2 users, 1 workspace, 5 deployments, and 500 serverless credits/month.
A genuinely free hosted tier lets small teams run production workloads indefinitely without payment, not just evaluate for a limited window.
Programming model
Dagster: Pipelines are modeled as assets across the technology stack rather than via a specific language decorator pattern documented here.
Prefect: Existing Python functions are turned into orchestrated workflows via an @flow decorator, without a new framework or DSL.
A decorator-based approach lets teams add orchestration to code they already have with minimal rewriting.
Pricing transparency beyond the entry tier
Dagster: Publishes pricing for Solo ($120/month) and Starter ($1,200/month) tiers, with Enterprise as custom.
Prefect: Only the free Hobby tier's pricing is published; Starter, Team, and Pro Cloud tier pricing is not disclosed.
Published mid-tier pricing lets buyers budget and compare costs before a sales conversation.
AI-assisted operations
Dagster: Dagster+ AI provides AI-assisted diagnostics and automated remediation for pipeline issues.
Prefect: No AI-assisted diagnostics feature is documented for Prefect.
Built-in AI diagnostics can reduce manual triage time when pipelines fail.
Asset-based model gives built-in lineage and observability other orchestrators require add-ons for.
Strong local development and testing experience for Python-based pipelines.
Free, fully-featured open-source core with no artificial feature gating.
Post-acquisition, Prefect has committed to continued investment and unchanged pricing.
Cons
The asset-centric abstraction has a steeper learning curve than simpler task-based schedulers.
Dagster+ credit-based pricing can be harder to forecast than flat per-seat pricing at scale.
Enterprise pricing is not publicly listed and requires a sales conversation.
Recent acquisition by Prefect introduces some uncertainty about long-term product direction, despite stated commitments.
Prefect
Pros
Fully open-source core under a permissive Apache 2.0 license
No proprietary DSL; pipelines are just Python functions
Hybrid execution keeps code and data inside your own infrastructure
Free Hobby tier and self-hosting keep the entry cost low
Scales to enterprise needs with SSO, RBAC, and an uptime SLA
Cons
Pricing increases sharply from the Team plan to custom-priced Enterprise
Serverless credit/minute-based billing can be harder to predict than flat pricing
Smaller plugin and connector ecosystem than Apache Airflow's long-established community
Self-hosting requires managing your own infrastructure, scaling, and updates
Some enterprise features and the hosted UI are Cloud-only, not part of the open-source core
Use Cases
Choose Dagster: Teams that want asset-lineage-first orchestration with native dbt, Snowflake, and Fivetran hooks, branch deployments for testing pipeline changes, and AI-assisted pipeline diagnostics, and who are prepared to pay from day one (Dagster+ has no permanent free tier).
Choose Prefect: Teams that want to start free on the Hobby plan and add orchestration to existing Python code via a decorator rather than restructuring pipelines around assets, and who value a large open-source community (40,000+ GitHub stars).
Need both: Given the acquisition, most teams won't need both going forward, but organizations mid-migration between the two frameworks — or evaluating consolidation in the wake of Prefect's acquisition of Dagster Labs — may run both temporarily.
Dagster
Modern ETL/ELT orchestration — Teams use Dagster to orchestrate ingestion, transformation (often via dbt), and loading into warehouses like Snowflake or BigQuery with built-in lineage.
ML and AI pipeline orchestration — Dagster orchestrates feature engineering, model training, and increasingly RAG or agentic LLM pipelines as declarative asset graphs.
Data platform observability and lineage — Organizations use Dagster's asset catalog and lineage graph to understand data freshness and dependencies across many pipelines from one place.
Prefect
Data pipeline orchestration — Schedules and monitors ETL/ELT pipelines with automatic retries and failure alerting.
ML and AI pipeline scheduling — Orchestrates model training, evaluation, and agentic workflows with observability across runs.
Hybrid, security-conscious orchestration — Runs workflow code inside a company's own VPC while using Prefect Cloud only for scheduling and monitoring.
Frequently Asked Questions
Is Dagster related to Prefect?
Yes — both companies' FAQs state that Prefect acquired Dagster Labs, the company behind Dagster, in July 2026.
Do Dagster and Prefect have free plans?
Prefect offers a free Hobby plan ($0) on Prefect Cloud, plus a free open-source core. Dagster's open-source framework is free to self-host, but Dagster+ has no permanent free tier — only a 30-day trial before paid plans begin at $120/month.
What language does Prefect use?
Prefect workflows are written in Python, turned into orchestrated flows via the @flow decorator.
How large is Prefect's open-source community?
The Prefect framework is open source (Apache 2.0) with 40,000+ GitHub stars.
Does Dagster+ offer a free trial?
Yes, a 30-day free trial is available for the Solo and Starter plans.
What data tools does Dagster integrate with?
Dagster lists first-class integrations with dbt, Snowflake, and Fivetran.