Airflow VS Pandas

Compare Airflow vs Pandas and see what are their differences.

Airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows (by apache)

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more (by pandas-dev)
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Airflow Pandas
59 123
23,923 31,887
1.6% 0.9%
10.0 10.0
4 days ago about 3 hours ago
Python Python
Apache License 2.0 BSD 3-clause "New" or "Revised" 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.

Airflow

Posts with mentions or reviews of Airflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-09.

Pandas

Posts with mentions or reviews of Pandas. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-02.

What are some alternatives?

When comparing Airflow and Pandas you can also consider the following projects:

Kedro - A Python framework for creating reproducible, maintainable and modular data science code.

Cubes - Light-weight Python OLAP framework for multi-dimensional data analysis

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

luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

dagster - An orchestration platform for the development, production, and observation of data assets.

Dask - Parallel computing with task scheduling

NumPy - The fundamental package for scientific computing with Python.

SymPy - A computer algebra system written in pure Python

blaze - NumPy and Pandas interface to Big Data

pyexcel - Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files

Apache Camel - Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data.