Software Alternatives, Accelerators & Startups

DataMelt VS Anaconda

Compare DataMelt VS Anaconda and see what are their differences

DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.

Anaconda logo Anaconda

Anaconda is the leading open data science platform powered by Python.
  • 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

  • Anaconda Landing page
    Landing page //
    2023-09-22

DataMelt

$ Details
freemium
Platforms
Linux Windows Mac OSX Java Cross Platform
Release Date
2020 June

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Anaconda videos

Anaconda - Good Bad Flicks

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  • Review - ANACONDA BAD MOVIE REVIEW | Double Toasted
  • Review - Anaconda - Good Bad or Bad Bad #23

Category Popularity

0-100% (relative to DataMelt and Anaconda)
Technical Computing
100 100%
0% 0
IDE
0 0%
100% 100
Numerical Computation
100 100%
0% 0
Data Science And Machine Learning

Questions and Answers

As answered by people managing DataMelt and Anaconda.

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

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Reviews

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

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

Anaconda Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: Anaconda offers its data science and machine learning capabilities via a number of different product editions. Its flagship product is Anaconda Enterprise, an open-source Python and R-focused platform. The tool enables you to perform data science and machine learning on Linux, Windows, and Mac OS. Anaconda allows users to download more than 1,500 Python and R...

What are some alternatives?

When comparing DataMelt and Anaconda, you can also consider the following products

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

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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.

PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...