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DataMelt VS Statista

Compare DataMelt VS Statista and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

DataMelt logo DataMelt

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

Statista logo Statista

The Statistics Portal for Market Data, Market Research and Market Studies
  • 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

  • Statista Landing page
    Landing page //
    2023-07-17

DataMelt videos

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Statista videos

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Finding Statistics with STATISTA

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Category Popularity

0-100% (relative to DataMelt and Statista)

DataMelt

Statista

Technical Computing
47 47%
Technical Computing
53% 53
Business & Commerce
0 0%
Business & Commerce
100% 100
Numerical Computation
100 100%
Numerical Computation
0% 0
Office & Productivity
100 100%
Office & Productivity
0% 0

Questions and Answers

As answered by people managing DataMelt and Statista.

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 DataMelt and Statista. 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 DataMelt and Statista

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

Statista Reviews

We have no reviews of Statista yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Statista seems to be more popular. It has been mentiond 98 times 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.

DataMelt mentions (0)

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

Statista mentions (98)

  • What is Email List Building? Everything You Need to Know.
    As of 2025, Statista.com projects a staggering 4.6 billion email users, highlighting the enduring power of email marketing. This blog is your guide to understanding and mastering email list building. Explore its significance, learn best practices, and glean actionable insights from real successes. Source: 6 months ago
  • Why do people keep blaming the UCP for homelessness and drug overdoses when these problems are same or worse in BC which has an NDP government?
    I can't speak for everyone here, but I doubt that most people are spending $79 USD/mo for a statista.com subscription. Source: 11 months ago
  • Women are hypergamous not for wanting the best man, but for not really having an upper limit on the qualities they desire in men
    The proof that the data doesn't exist? Go to statista.com and look for "bumble height" or any other search term you think is needed to find that chart. Then reflect on how nothing on the chart is how a scientific outlet would do a chart, and especially not Statista. This is done by an amateur who has no idea about designing charts that meet any scientific standard. Source: 11 months ago
  • With MUCH less marketing and MUCH smaller markets....the Women's College Basketball Finals absolutely crushed the NHL's playoff ratings.
    Outside of 2019/20 (COVID), revenue has been rising steadily. (statista.com). Source: 12 months ago
  • Samsung's use of poo poo FedEx is frustrating
    For those who aren't aware, FedEx Ground is made up of independent contractors. FedEx Express is the original FedEx. Yes, by nature of the business, if you ship something FedEx ground it takes longer, and the longer it takes and the more hands that handle a package the more chance there is for loss, damage, or delay. If you ship something through FedEx Express you generally get things much faster and have a better... Source: about 1 year ago
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What are some alternatives?

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

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

datarobot - Become an AI-Driven Enterprise with Automated Machine Learning

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

Montecarlito - MonteCarlito is a free Excel-add-in to do Monte-Carlo-simulations.

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.

Statwing - Simply upload your spreadsheet or dataset, then select the relationships you want to explore. Statwing was built by and for analysts, so you can clean data, explore relationships, and create charts in minutes instead of hours.

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