SaaStalky
DA logo

Dagster

Open-source orchestration for data pipelines and workflows

Data EngineeringOrchestration

What Dagster does

Dagster is an open-source platform focused on orchestrating data pipelines and managing data workflows. It is used by data engineering teams to design, schedule and monitor complex sequences of data tasks, ensuring reliability and traceability. Orchestration tools like Dagster are typically used to coordinate processes across different data sources and systems, with features for development, testing, and deploying workflows. The project is well-recognised within the open-source data engineering community and is suited to technical teams needing a programmable, modular approach. It fits in the orchestration segment alongside tools like Apache Airflow and Prefect, appealing to users looking for modern workflow management backed by active development.

What sets it apart

Dagster offers a modular, developer-focused approach to pipeline orchestration with open-source flexibility.

Key features

  • Task scheduling and orchestration
  • Pipeline monitoring
  • Modular workflow design
  • Observability tools
  • Code-defined pipelines

What teams use it for

  • Orchestrate ETL workflows
  • Schedule routine data jobs
  • Monitor pipeline health
  • Develop and test modular data workflows

Pros

  • +Open-source and extensible
  • +Strong community support
  • +Granular pipeline observability
  • +Supports code-driven development

Cons

  • Steep learning curve for new users
  • Best suited to engineering-heavy teams
  • UI not optimised for non-technical users

Integrates with

dbtApache SparkAWS S3Airflow

Our verdict

Ideal for teams seeking open-source orchestration with strong developer tooling and code-based workflows. Those wanting a non-technical interface or simpler project setup may prefer alternatives.

Frequently asked questions

Is Dagster open-source?+

Yes, Dagster is open-source and can be self-hosted.

Who typically uses Dagster?+

It is designed for data engineering teams needing to manage, schedule, and monitor complex data pipelines.

How does Dagster compare to Apache Airflow?+

Dagster emphasises a modern, code-first workflow and modular design, while Airflow focuses on task scheduling with a longer legacy in orchestration. Suitability depends on your team's technical preferences.

Where can I find Dagster's pricing or hosting options?+

For details on pricing or hosting, consult Dagster's official website.

Dagster alternatives

Similar tools worth comparing.

Compare side by side →
AA logo

Managed Apache Airflow for scaling data pipelines

Managed Apache Airflow

Custom pricing
PR logo

Orchestrate, schedule and monitor complex data workflows

Workflow orchestration

Custom pricing
CC logo

Managed Apache Kafka service for real-time data streaming

Managed Kafka

Custom pricing
MA logo

SQL database for real-time streaming data analysis

Streaming database

Custom pricing

We link directly to each vendor's own site. These are not affiliate or tracking links, and we earn no commission from them.