pyStudio VS dagster-example-pipeline

Compare pyStudio vs dagster-example-pipeline and see what are their differences.

pyStudio

The easier way to do machine learning in Python without coding! (by elmpystudio)

dagster-example-pipeline

Template Dagster repo using poetry and a single Docker container; works well with CICD (by MileTwo)
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pyStudio dagster-example-pipeline
6 1
115 64
-1.7% -
7.8 0.0
7 months ago about 2 years ago
Python Python
GNU General Public License v3.0 only Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pyStudio

Posts with mentions or reviews of pyStudio. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-01.

dagster-example-pipeline

Posts with mentions or reviews of dagster-example-pipeline. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-25.

What are some alternatives?

When comparing pyStudio and dagster-example-pipeline you can also consider the following projects:

orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis

mlrun - MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

canarypy - CanaryPy - A light and powerful canary release for Data Pipelines

Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]