dagster
Active·★ 15.9k·Apache-2.0·Updated 2026-07-16
★ Most Popular★ Trending★ Essential
Dagster is a data orchestrator purpose-built for data platforms in the MLOps era, helping users define, develop, and operate data assets. It offers a powerful programming model, local development experience, and a robust UI for observing and debugging pipelines in production.
dagster is currently grouped under Workflow Automation, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Software-defined Assets and Building reliable data platforms. The listed license is Apache-2.0, which is useful when adoption constraints matter. It also shows measurable community traction with 15.9k GitHub stars.
#Data Orchestration#MLOps#Data Pipelines#ETL#Python#Coding#Data Analysis
01
Features
01Software-defined Assets
02Declarative Programming Model
03Powerful Local Development
04Robust Operational UI (Dagit)
05Extensive Integrations
02
Why choose it
+Software-defined Assets
+Building reliable data platforms
+Covers 7 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a Apache-2.0 license, which makes adoption and review easier.
03
Trade-offs
!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04
Compatibility
Snowflake
Supported
Verified via docs
Spark
Supported
Verified via docs
Kubernetes
Supported
Verified via docs
dbt
Supported
Verified via docs
Airbyte
Supported
Verified via docs
Scikit-learn
Supported
Verified via docs
05
Quick start
1
$ pip install dagster dagster-webserver
06
Use cases
↳Building reliable data platforms
↳Developing MLOps workflows
↳Automating data analytics and reporting
07
How it compares
≈dagster sits in the Workflow Automation category, so it makes more sense to evaluate it alongside tools like Gemini CLI instead of in isolation.
≈If your main need is closer to "Building reliable data platforms", that use case is a better lens for comparison than broad feature checklists alone.
≈dagster uses a Apache-2.0 license, and community traction are both easier to judge in category context.
08
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