cool VS mara-pipelines

Compare cool vs mara-pipelines and see what are their differences.

cool

Make Python code cooler. Less is more. (by abersheeran)

mara-pipelines

A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow (by mara)
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cool mara-pipelines
1 3
116 2,056
- 0.3%
1.1 6.0
about 1 year ago 5 months ago
Python Python
Apache License 2.0 MIT License
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.

cool

Posts with mentions or reviews of cool. We have used some of these posts to build our list of alternatives and similar projects.

mara-pipelines

Posts with mentions or reviews of mara-pipelines. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-22.

What are some alternatives?

When comparing cool and mara-pipelines you can also consider the following projects:

Prefect - The easiest way to build, run, and monitor data pipelines at scale.

abcd-hcp-pipeline - bids application for processing functional MRI data, robust to scanner, acquisition and age variability.

PyFunctional - Python library for creating data pipelines with chain functional programming

kuwala - Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demographics data b) Point of Interests from Open Street Map c) Google Popular Times

papermill - 📚 Parameterize, execute, and analyze notebooks

pybaseball - Pull current and historical baseball statistics using Python (Statcast, Baseball Reference, FanGraphs)

dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration

dremio-oss - Dremio - the missing link in modern data

airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.

citus - Distributed PostgreSQL as an extension

sgr - sgr (command line client for Splitgraph) and the splitgraph Python library