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DataMelt VS GNU Make

Compare DataMelt VS GNU Make and see what are their differences

DataMelt

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

Rating
5.0 · 1 review
Pricing
Open source Freemium Free trial
Alternatives Is it good?
GNU Make

GNU Make is a tool which controls the generation of executables and other non-source files of a program from the program's source files.

Rating
0 reviews
Alternatives Is it good?
Data Analytic System
Sourced crypto market data with indicator monitoring, market regime context and research. BTC, ETH, XRP, SOL + major indices monitored 24/7. Educational content — not investment advice. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Technical Computing popularity
100% vs 0%
alternatives listed
44 vs 98

Base details

Website, pricing, platforms and company facts side by side.

DataMelt
GNU Make
Website datamelt.org gnu.org
Pricing
Open source Freemium Free trial
—
Platforms
Linux Windows Mac OSX Java Cross Platform +2
—
Company 2020 —
Listed in
Technical Computing Numerical Computation Data Dashboard Machine Data Analytics Statistics Data Visualization Predictive Analytics +4
Front End Package Manager JavaScript Package Manager JS Build Tools Package Manager +1

About DataMelt and GNU Make

In their own words, as submitted to SaaSHub.

DataMelt
GNU Make

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...

Read more about DataMelt

No description of GNU Make yet.

Features and specs

What each product offers, as listed by its team.

DataMelt 5 features
GNU Make 5 features
  • Versatility
    DataMelt supports a wide range of programming languages including Java, Jython, Groovy, and JRuby, making it versatile for users familiar with different coding environments.
  • Rich Libraries
    It offers a comprehensive set of scientific libraries for numerical computation, data analysis, and visualization, which can be beneficial for complex scientific research and data processing tasks.
  • Cross-Platform
    DataMelt is platform-independent, running on any operating system that supports Java, such as Windows, macOS, and Linux. This makes it accessible to a wide audience.
  • Integrated Development Environment
    DataMelt provides a powerful IDE that integrates coding, plotting, and visualization tools, streamlining the workflow for developers and researchers.
  • Free and Open Source
    The core functionality of DataMelt is available for free, which can be appealing to individuals and organizations looking for budget-friendly computational tools.
  • Portability
    GNU Make is highly portable and can be used across various Unix-like operating systems as well as on Windows.
  • Dependency Management
    It efficiently handles complex dependencies between various parts of the software, ensuring that changes are propagated properly.
  • Open Source
    Being open-source software, GNU Make is freely available and can be modified according to user needs.
  • Wide Adoption
    It is widely adopted in the industry, which means that there is extensive documentation and a large community for support.
  • Efficiency
    GNU Make speeds up the build process by only recompiling the necessary parts of the codebase.

Possible disadvantages

  • Complex Syntax
    The syntax of GNU Makefiles can become very complex, especially for large projects, making them hard to read and maintain.
  • Limited Cross-Platform Scripting
    While the tool itself is cross-platform, Makefiles can sometimes include shell commands that are not portable.
  • Steep Learning Curve
    Beginners may find it challenging to grasp the concepts and syntax of GNU Make, leading to a steep learning curve.
  • Debugging Difficulty
    Debugging Makefiles can be difficult, with limited tools available to trace or step through the make process.
  • Performance Bottlenecks
    For extremely large projects, performance can become an issue, as the evaluation of dependencies might become slow.

Analysis

An editorial look at what each product does well and who it suits.

DataMelt
GNU Make

No analysis of DataMelt yet.

Overall verdict

  • Yes, GNU Make is a robust and reliable tool for managing build processes. Its long-established reputation and widespread use in both open-source and commercial projects underline its effectiveness and flexibility.

Why this product is good

  • GNU Make is widely used because it automates the build process, efficiently handling dependencies and detecting minimal sets of changes in source files. It is highly customizable, supports non-recursive builds, and integrates well into various development environments.

Recommended for

  • Software developers working on C/C++ projects
  • Teams looking to automate build processes
  • Projects that require cross-platform build capabilities
  • Developers who prefer command-line tools
  • Open-source project maintainers

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
DataMelt
GNU Make
100% 100%
Technical Computing
0% 0%
0% 0%
JS Build Tools
100% 100%
100% 100%
Office & Productivity
0% 0%
0% 0%
Front End Package Manager
100% 100%

Questions & Answers

As answered by people managing DataMelt and GNU Make.

How would you describe the primary audience of your product?

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 GNU Make. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

DataMelt 5.0 · 1 review
GNU Make no reviews yet
  • Great 3D graphics
    SaaSHub review
    · Dec 2019

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

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

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