Cubes VS Dask

Compare Cubes vs Dask and see what are their differences.

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Cubes Dask
1 32
1,490 12,022
0.0% 0.8%
0.0 9.6
about 2 years ago 1 day ago
Python Python
Creative Commons Public Domain Dedication and Certification 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.

Cubes

Posts with mentions or reviews of Cubes. We have used some of these posts to build our list of alternatives and similar projects.
  • Building data analysis apps
    1 project | /r/Python | 16 Apr 2021
    I'm looking for materials and tools to learn. I'm reading up on OLAP and cubes. I found cubes python package but it hasn't been updated in years. Could you give me some tips on what to learn in 2021?

Dask

Posts with mentions or reviews of Dask. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-15.

What are some alternatives?

When comparing Cubes and Dask you can also consider the following projects:

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

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

NumPy - The fundamental package for scientific computing with Python.

Numba - NumPy aware dynamic Python compiler using LLVM

Bubbles - [NOT MAINTAINED] Bubbles – Python ETL framework

Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python

NetworkX - Network Analysis in Python

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

blaze - NumPy and Pandas interface to Big Data