Dagster is an open-source data orchestrator that models data assets and coordinates their development, execution, lineage, and monitoring. Dagster+ adds hosted and hybrid deployment options.
Product documentation verifies asset orchestration, integrations, deployment choices, and tiered usage pricing. Public G2 coverage is limited to two reviews, too few for a reliable sentiment estimate.
This profile combines documented product information and independent evidence where available. It is not a hands-on test unless TechZella explicitly identifies one.
Dagster is an open-source orchestrator for developing, running, and observing data assets. Its asset-oriented model connects produced data, dependencies, and executions, rather than representing pipeline work only as a sequence of tasks.
Teams can use Dagster locally or self-host it, while Dagster+ adds hosted serverless and hybrid deployment. Dagster’s official integration catalog includes dbt, Snowflake, Fivetran, Databricks, AWS, and other data tools.
Prefect announced its acquisition of Dagster Labs on July 13, 2026. The announcement said Dagster would remain supported under its own name and open-source license.
A quick way to understand who this product may suit, where its limits matter, and which facts are most relevant before you compare alternatives.
Python-oriented data teams coordinating dbt, ingestion, machine-learning, and warehouse assets that need explicit dependencies, lineage, checks, and operational visibility.
Teams seeking a simple, non-code scheduler may find Dagster's Python-oriented asset model and self-managed deployment responsibilities a poor match. Dagster+ usage charges also require teams to estimate asset and operation activity, and should evaluate alternatives such as Prefect or Apache Airflow instead.
AWS, Cloud, Docker, Kubernetes, Python
7.7/10
These are the product-specific differences that may matter when deciding whether the software fits your workflow. They are based on documented evidence rather than a universal ranking.
These are documented constraints or practical friction points that may matter before you adopt the product.
Credit use depends on asset materializations and operation executions, so projected workflow activity affects recurring spend.
Evidence source ↗Teams building external automation against it should review version changes and avoid assuming every endpoint is a stable public contract.
Evidence source ↗Buyers should track future ownership communications while noting that the announcement said no immediate migration or deployment change was required.
Evidence source ↗Dagster's core repository is Apache 2.0 licensed and can be self-hosted. Infrastructure and operations are the user's responsibility.
Check current pricing →One user, one code location, and one deployment. Includes usage charges of $0.040 per credit; serverless compute is $0.010 per minute.
Check current pricing →Up to three users, five code locations, and one deployment. Includes usage charges of $0.035 per credit; serverless compute is $0.010 per minute.
Check current pricing →Enterprise plan with custom serverless compute, unlimited code locations and deployments, personalized onboarding, and uptime SLAs.
Check current pricing →Pricing may change. Verify current plans on the vendor's website.
Compare similar products directly, then see which alternatives may make more sense when your requirements differ.
| Decision factor | Dagster | Prefect | Apache Airflow |
|---|---|---|---|
| Workflow model | Models data products as assets and their dependencies. | Organizes Python workflows around flows and tasks. Source ↗ | Represents workflows as DAGs of tasks and dependencies. Source ↗ |
| Deployment model | Dagster+ offers serverless or hybrid deployment; open-source Dagster can be self-hosted. | Prefect Cloud offers managed workflows, while Prefect also documents open-source self-hosted options. Source ↗ | Airflow documentation describes deployments assembled from scheduler, API server, processor, and other components, including Docker and Kubernetes options. Source ↗ |
| Published cloud pricing | Dagster+ Solo starts at $10 per month plus usage credits; Starter starts at $100 per month plus credits. | Prefect Cloud lists a free Hobby plan and a $100 per month Starter plan. Source ↗ | Not documented |
| License and pricing model | Dagster's open-source repository is Apache 2.0 licensed; Dagster+ has paid usage-based plans. | Not documented | Apache Airflow is open-source software; the reviewed project documentation does not publish a managed-service price. Source ↗ |
Only factors supported by the available research are shown. The comparison is descriptive, not a ranking.
These products address broadly similar requirements. The descriptions focus on documented reasons a buyer might compare them with Dagster.
| License | Apache 2.0 for open-source repository |
|---|---|
| API | GraphQL; documented as evolving |
| Primary development language | Python |
| Hosted deployment | Dagster+ serverless or hybrid |
| Hybrid agent environments | ECS, Docker, Kubernetes, local |
| Free trial | 30 days for Dagster+ |
| Usage metric | Credits based on asset materializations and operations executed |
| Integrations | dbt, Snowflake, Fivetran, Databricks, AWS, Azure, Airbyte, and others |
Verified installation, hosting, administration, or environment details that can affect implementation.
| Hosted and hybrid options | Dagster+ offers serverless deployments or hybrid deployments with the backend hosted and an agent running in the customer's environment. Source ↗ |
|---|---|
| Hybrid agent backends | Documented agent backends include ECS, Docker, Kubernetes, and local processes. Source ↗ |
Documented portability, standards, export, or switching considerations. No switching-cost score is shown unless the evidence supports one.
Dagster describes Airlift capabilities for viewing Airflow execution alongside Dagster workflows and converting existing Airflow DAGs into Dagster assets.
Evidence source ↗Dagster+ lists data portability in its plan comparison; the reviewed public page does not specify export formats or migration procedures.
Evidence source ↗A proprietary editorial score based on product capabilities, usability, value, performance, support and user sentiment evidence.
Product documentation verifies asset orchestration, integrations, deployment choices, and tiered usage pricing. Public G2 coverage is limited to two reviews, too few for a reliable sentiment estimate.
Methodology v1.0. The assessment weighs feature coverage (25%), ease of use (15%), value for money (20%), performance (15%), support (10%) and user sentiment (15%), using researched product evidence and verified review evidence where available. It is a TechZella editorial assessment, not a direct user-review average.
Key claims are linked to the sources used to verify them. This evidence record is separate from third-party user ratings.
TechZella evaluates software using documented product capabilities, pricing information, usability and value considerations, independent user evidence where available, and competitive context. The assessment is an editorial review, not a hands-on test unless one is explicitly identified. Our editorial assessment is based on 5 documented sources.
The official repository identifies the Apache-2.0 license.
View source ↗Verified 2026-11-11The official pricing page lists monthly plan fees, per-credit rates, and serverless compute pricing.
View source ↗Verified 2026-11-11The pricing page lists a 30-day trial for Solo and Starter and states a 30-day trial is available.
View source ↗Verified 2026-11-11The official integrations page lists these integration guides and libraries.
View source ↗Verified 2026-11-11Official documentation describes supported queries and mutations and cautions that the API is evolving.
View source ↗Verified 2026-11-11The official Dagster announcement says Dagster remains a supported product and its open-source project keeps its existing license.
View source ↗Verified 2026-11-11Answers begin with the clearest available response, followed by the context that helps you act on it.
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