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VC Starter Kit VS DataMelt

Compare VC Starter Kit VS DataMelt and see what are their differences

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Contents:
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  2. » Reviews
  3. » Alternatives

VC Starter Kit logo VC Starter Kit

Everything you need to look like a Venture Capitalist

DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.
  • VC Starter Kit Landing page
    Landing page //
    2023-05-13
  • DataMelt Landing page
    Landing page //
    2019-07-18

DataMelt is a Java program for statistics, general data analysis and data visualization. The program is often termed "computational platform" since it can be used with different programming languages (Java, Python, Groovy..). DataMelt is not limited to a single programming language. The program is used for numeric computation, statistics, analysis of large data volumes ("big data") and scientific visualization. Full description: https://handwiki.org/wiki/Software:DataMelt

Category Popularity

0-100% (relative to VC Starter Kit and DataMelt)

VC Starter Kit

DataMelt

Windows Tools
100 100%
Windows Tools
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Productivity
100 100%
Productivity
0% 0
Numerical Computation
0 0%
Numerical Computation
100% 100

Questions and Answers

As answered by people managing VC Starter Kit and DataMelt.

How would you describe your primary audience?

DataMelt's answer:

students and data scientists

What's the story behind your product?

DataMelt's answer:

DataMelt has its roots in particle physics where data mining is a primary task. It was created as Software:jHepWork project in 2005 and it was initially written for data analysis for particle physics.

What makes your product unique?

DataMelt's answer:

Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby

Why should a person choose your product over its competitors?

DataMelt's answer:

Large database of examples and code snippets https://datamelt.org/code/

Who are some of the biggest customers of your product?

DataMelt's answer:

Students at universities and data scientists.

Which are the primary technologies used for building your product?

DataMelt's answer:

Java (JDK any new new release including JDK20)

User comments

Share your experience with using VC Starter Kit and DataMelt. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare VC Starter Kit and DataMelt

VC Starter Kit Reviews

We have no reviews of VC Starter Kit yet.
Be the first one to post

DataMelt Reviews

  1. Great 3D graphics

    I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples

Social recommendations and mentions

Based on our record, VC Starter Kit seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

VC Starter Kit mentions (1)

  • Allbirds S-1 IPO
    Whenever I hear about Allbirds, I can't but laugh and think about this site: https://vcstarterkit.com. - Source: Hacker News / almost 3 years ago

DataMelt mentions (0)

We have not tracked any mentions of DataMelt yet. Tracking of DataMelt recommendations started around Mar 2021.

What are some alternatives?

When comparing VC Starter Kit and DataMelt, you can also consider the following products

SmartWindows.app - Auto arrange all your app windows, whether on one screen or many with a single click!

SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.

SANeForce - SAN Pharma Sales Force Automation

LabPlot - LabPlot is a KDE-application for interactive graphing and analysis of scientific data.

PingPoint - Never miss a Mark Zuckerberg signup to your app ever again

RJS Graph - RJS Graph is an artificial intelligence-based data management platform that allows users or developers to organize the data by manipulating the binaries, scientific, mathematical, and other insights with accurate results.

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