What is Dagster?
Dagster is a data orchestration platform for building, running, and observing ETL/ELT and AI/ML pipelines.
It orchestrates transformations across dbt, Databricks, and Python, and moves data between SaaS sources and warehouses such as Snowflake and BigQuery.
Features include pipeline scheduling, experiment tracking, model training workflows, and real-time health metrics for freshness, performance, cost, and reliability.
Built-in observability provides dataset lineage, auto-generated documentation, alerting with Slack integration, and tools for impact analysis and debugging.
The data catalog and lineage tools help teams discover datasets, assign ownership, and maintain up-to-date metadata.
Compass surfaces context-aware answers from warehouse data for business users while governance is enforced via GitOps and team-level controls.
Dagster details
- Company
- Elementl, Inc.
- Jurisdiction
- State of California
- Built for
- Individuals
Dagster tech specs
- Integrations
- Slack GitHub
Dagster pricing
Free trial- Free trial
- 30 days
Verify on the official pricing page.
Start free trialDagster's key features
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Unified control plane for building, scaling, and observing AI and data pipelines
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Orchestration of ETL/ELT pipelines and data transformations (dbt, Databricks, Python) with integrations to warehouses like Snowflake and BigQuery
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Native support for AI/ML workflows including data preparation, model training, and experiment tracking
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Integrated observability and lineage with built-in lineage, real-time health metrics, alerting, and auto-generated dataset documentation
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Enterprise-grade security and deployment: SSO, RBAC, SCIM, SAML, SOC 2/HIPAA compliance, multi-tenant deployments, audit logs, and flexible cloud/region deployment options
Dagster use cases
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Orchestrate end-to-end ETL/ELT workflows with Dagster, integrating dbt, Databricks, Python and SaaS sources to load and transform data into your warehouse, schedule jobs, monitor runs and dataset lineage, and enforce governance and enterprise security
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Automate AI/ML pipeline orchestration using Dagster to coordinate data ingestion, feature engineering, distributed model training on Databricks, model lineage and versioning, and continuous retraining with real-time observability and alerts
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Centralize dataset cataloging and compliance by using Dagster to capture metadata and lineage across pipelines, provide searchable data catalogs for analysts, apply access controls and governance policies, and monitor data quality and provenance in production
Dagster user reviews
Would you recommend Dagster?
Who is Dagster for?
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Data engineers
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Data scientists
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Ml engineers
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Analytics engineers
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Data platform teams
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Enterprise data teams
Dagster FAQ
Is Dagster free?
Not permanently. Dagster gives you a free trial of 30 days, after which a paid plan is required. Plans include Solo plan at $10/mo, Starter plan at $100/mo, Popular solo plan at $120/mo and Starter at $1200/mo.
Is Dagster safe to use?
Dagster is operated by Elementl, Inc., registered in State of California. It has a substantial audience that is independently measured month to month.
What are the best alternatives to Dagster?
The closest alternatives to Dagster are Airbyte, Tredence.com and Lume AI. You can compare them side by side in the alternatives section further down this page.
What does Dagster do with my data?
Its privacy policy states that personal data is not sold or shared for marketing purposes. Data may be shared with third-party service providers that help run the product.
Who made Dagster?
Dagster is built and operated by Elementl, Inc., a company registered in State of California.
What does Dagster integrate with?
Dagster connects with Slack and GitHub.
Compliance, privacy and billing terms are as stated in each product's own published documentation and have not been independently verified by TopAI.tools.
