
Apache Airflow
Prefect.io
Luigi
Kestra.io
AWS Step Functions
Apache NiFi
Make.com
The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.

Developer documentation that anyone can edit

Which is more popular?
Based on our record, Dagster seems to be more popular. It has been mentioned 7 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | dagster.io | opendevdocs.com |
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What each product offers, as listed by its team.


Possible disadvantages
No features have been listed yet.
An editorial look at what each product does well and who it suits.


No analysis of Dagster yet.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
Airflow Vs. Dagster: The Full Breakdown!
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How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using Dagster and Open Devdocs. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Dagster is an open-source data orchestration system that allows users to define their data assets as Python functions. Once defined, Dagster manages and executes these functions based on a user-defined schedule or in...
Unlike Airflow, which supports any production environment, Dagster concentrates on cloud services and supports modern data stacks. Being cloud-native and container-native, this solution makes the scheduling and...
Dagster is a Machine Learning, Analytics, and ETL Data Orchestrator. Since it handles the basic function of scheduling, effectively ordering, and monitoring computations, Dagster can be used as an alternative or...
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Recommendations tracked on public social media and blogs since March 2021.


If you run Dagster pipelines in production, you've probably wanted distributed tracing at some point — seeing exactly how long each op/asset took, how steps nest across a run, and how a run connects to whatever triggered it (a sensor... - Source: dev.to / about 18 hours ago
At my organization, which collects large volumes of public web data, we’ve developed a robust system for automated data quality checks using two powerful open-source tools: Dagster and Great Expectations. These tools are the cornerstone... - Source: dev.to / 12 months ago
Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different... - Source: dev.to / over 1 year ago
Tracking Open Devdocs since Jan 2023.
When comparing Dagster and Open Devdocs, you can also consider the following products.

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Compare Apache Airflow to Dagster or Open Devdocs:

Prefect offers modern workflow orchestration tools for building, observing & reacting to data pipelines efficiently.
Compare Prefect.io to Dagster or Open Devdocs:

Luigi is a Python module that helps you build complex pipelines of batch jobs.
Compare Luigi to Dagster or Open Devdocs:

Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
Compare Kestra.io to Dagster or Open Devdocs:

AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows.
Compare AWS Step Functions to Dagster or Open Devdocs:

An easy to use, powerful, and reliable system to process and distribute data.
Compare Apache NiFi to Dagster or Open Devdocs: