# Dagster

> A unified control plane for teams to build, scale, and observe AI and data pipelines with confidence.

Dagster is a unified control plane for building, scaling, and observing AI and data pipelines. It provides teams with an asset-based orchestration framework that supports ETL/ELT pipelines, data transformations, and AI/ML workflows. Trusted by companies like Kraft Heinz, Vanta, Bayer, and AMD, Dagster enables data teams to deliver insights faster while maintaining reliability and governance across their data platforms.

- **Asset-Based Orchestration** enables teams to define data assets declaratively, making pipelines easier to understand, test, and maintain with clear dependencies and lineage tracking.

- **Data Catalog & Lineage** empowers teams to discover and understand datasets with clear ownership, column-level lineage, and auto-generated documentation that stays current.

- **Monitoring & Alerting** keeps teams ahead of data incidents with intelligent alerts in Slack, streamlined resolution workflows, and AI-powered debugging with impact analysis.

- **Real-time Health Metrics** track freshness, performance, costs, and reliability to keep pipelines healthy and stakeholders confident in their data.

- **Branch Deployments** support local development workflows and CI/CD integration, allowing teams to test changes in isolated environments before production.

- **Event-Based Automations** trigger pipelines based on data events, schedules, or external signals for responsive data processing.

- **Partitions & Backfills** handle time-series and categorical data efficiently with built-in support for incremental processing and historical data reprocessing.

- **Data Quality Checks** validate asset freshness and quality with native checks and dbt test integration to catch issues before they impact downstream consumers.

- **Compass Feature** turns warehouse data into instant, trustworthy answers for stakeholders inside the tools they already use, governed by the data team through GitOps.

To get started, sign up for Dagster+ with a 30-day free trial or install the open-source version locally. Define your data assets using Python, configure integrations with your existing tools like dbt, Snowflake, or BigQuery, and deploy to production with serverless or hybrid deployment options.

## Features
- Asset-based orchestration
- Workflow-based orchestration
- Data catalog with lineage
- Column-level lineage
- Monitoring and alerting
- Real-time health metrics
- Branch deployments
- Event-based automations
- Partitions and backfills
- Asset quality checks
- Asset freshness checks
- dbt integration
- Catalog search
- Cost tracking for BigQuery and Snowflake
- Role-based access control
- SSO and SAML integration
- Audit logs
- Serverless deployments
- Hybrid deployment options
- AI-powered debugging

## Integrations
dbt, Snowflake, BigQuery, Databricks, Slack, Microsoft Teams, Google IdP, GitHub IdP, SAML IdPs, AWS, Python

## Platforms
WEB, API, LINUX, MACOS, WINDOWS

## Pricing
Open Source, Free tier available

## Links
- Website: https://dagster.io
- Documentation: https://docs.dagster.io
- Repository: https://github.com/dagster-io/dagster
- EveryDev.ai: https://www.everydev.ai/tools/dagster