Dagster

What it does

Dagster is an AI-native DataOps platform that orchestrates, observes, and activates data across your entire stack. Unlike traditional schedulers that only track whether a job finished, Dagster understands the assets those jobs produce by attaching lineage, quality signals, and dependency context to every piece of data your team builds. Its asset-centric model means it can automatically track lineage, surface data health, and show the full blast radius of a failure before it reaches anyone downstream. Dagster's core orchestration framework is open source, while Dagster+ is the managed cloud offering that adds branch deployments, hybrid deployment, role-based access control, cost insights, and built-in observability. It ships first-class integrations with tools like dbt, Snowflake, and Fivetran, and Dagster+AI uses the platform's context - assets, runs, lineage, freshness, and failures - to help teams diagnose issues faster.

How to use: Start with the open-source Dagster framework or sign up for a Dagster+ trial. Define your pipelines as software-defined assets, connect integrations such as dbt, Snowflake, or Fivetran, then schedule, run, and monitor everything from Dagster's UI with built-in lineage, catalog, and observability.

Core features

• ✦Asset-centric data orchestration
• ✦Integrated lineage and observability
• ✦Data catalog and data quality signals
• ✦Best-in-class testability (local testing, branch deployments)
• ✦Cost insights
• ✦Open-source core with Dagster+ managed cloud
• ✦First-class integrations with dbt, Snowflake, and Fivetran
• ✦Dagster+AI for diagnosing pipeline issues

Use cases

• →ETL/ELT Pipelines
• →AI & Machine Learning Workflows
• →Data Modernization
• →Building Data Products
• →Building Trustworthy AI Analytics