Dagster
Open SourceData orchestrator platform for building, scheduling, monitoring, and observing reliable asset-based data pipelines.
Informations sur l’outil
Qu'est-ce que Dagster ?
Dagster is the operational layer that structures how data is built, observed, and delivered so teams and AI agents can rely on trusted, reliable data pipelines across tools and infrastructure. It helps organizations build, schedule, and monitor reliable asset-based data pipelines with hybrid deployment and AI context support.
Fonctionnalités principales
Asset-based pipeline orchestration
Build and run asset-based pipelines across any tool in the stack, enabling engineers, stakeholders, and agents to work from the same operational foundation.
Built-in observability
Real-time monitoring, asset health dashboards, lineage, dependencies, quality signals, and failure context attached to every asset so teams can see data health across the platform.
Hybrid deployment
Run compute in your own infrastructure while Dagster manages the control plane, supporting cloud, on-prem, and hybrid setups without re-architecting for compliance.
Branch deployments
Ship pipeline changes without putting production at risk by validating every change in a production-like environment before it touches real data.
Composability and guardrails
Platform teams define standards once so downstream teams and AI-assisted workflows can build on top with consistency, testability, and governance by design.
Native dbt and Snowflake support
First-class integrations that orchestrate, monitor, and catalog existing dbt models and Snowflake assets without custom glue code.
AI-ready developer experience and Dagster+ AI
Local development with fast iteration plus Dagster+ AI that uses assets, runs, lineage, freshness, failures, and automation history so teams can diagnose issues and take action; includes Compass for governed data agents.
Data catalog and data quality
Platform capabilities for data catalog and data quality as part of the overall orchestration and observability layer.
Cas d'utilisation
- #1
ETL/ELT pipelines
Orchestrate and monitor ETL and ELT data pipelines with asset-based workflows and full visibility.
- #2
AI and machine learning
Support AI and ML workflows by providing trusted data context, lineage, and operational reliability for AI agents and models.
- #3
Data modernization
Modernize data platforms with scalable, composable orchestration, observability, and hybrid deployment options.
- #4
Data products
Build and deliver reliable data products with shared standards, guardrails, and operational context.
Plans tarifaires
Open source core available; free to get started; Dagster+ offering for advanced and enterprise capabilities; talk to sales and pricing page referenced for commercial options.
Alternatives
Foire aux questions
What is Dagster?
Is Dagster open source?
Does Dagster support hybrid deployment?
What integrations does Dagster offer?
How does Dagster help with AI and machine learning workflows?
Who is Dagster designed for?
Dagster Contacts et réseaux sociaux
- SociétéDagster Labs
- Adresse2 Embarcadero Ctr, San Francisco, CA, 94111, US
- Assistance
- Site Internet :
- Twitter
- YouTube
- LinkedIn
- GitHub
Avis
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