vg VS QuickQanava

Compare vg vs QuickQanava and see what are their differences.

vg

tools for working with genome variation graphs (by vgteam)
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vg QuickQanava
2 4
865 853
1.6% -
9.8 9.3
4 days ago 6 days ago
C++ C++
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
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.

vg

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

We haven't tracked posts mentioning vg yet.
Tracking mentions began in Dec 2020.

QuickQanava

Posts with mentions or reviews of QuickQanava. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-04.

What are some alternatives?

When comparing vg and QuickQanava you can also consider the following projects:

nodeeditor - Qt Node Editor. Dataflow programming framework

libgrape-lite - ๐Ÿ‡ A C++ library for parallel graph processing (GRAPE) ๐Ÿ‡

fdg - A Force Directed Graph Framework for Rust.

euler - A distributed graph deep learning framework.

Django - The Web framework for perfectionists with deadlines.

NetworkX - Network Analysis in Python

OpenCV - Open Source Computer Vision Library

Vue.js - ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

Keras - Deep Learning for humans

WeasyPrint - The awesome document factory

mintable - ๐Ÿƒ Automate your personal finances โ€“ for free, with no ads, and no data collection.

netsci-labs - (In progress) Network science laboratories. Covers graph theory, random graphs and ML on graphs