Software Alternatives, Accelerators & Startups

DataMelt VS Cachely.dev

Compare DataMelt VS Cachely.dev and see what are their differences

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DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.
Cachely is a managed implementation of self-hosted remote cache for monorepos. Speed up CI, prove how much time and cost you saved, get build optimization suggestions, safe from cache poisoning (CVE-2025-36852). Turborepo and Bazel on the roadmap.
  • 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

  • Cachely.dev Landing page
    Landing page //
    2026-08-01

Cachely is the managed self-hosted remote cache for Nx and Turborepo - the cache backend you'd otherwise build and run yourself, hosted for you on Cloudflare's edge (R2). It's a drop-in replacement for a DIY @nx/s3-cache / S3 bucket setup: point your build tool at Cachely with a token and two environment variables, and share build cache across CI and every developer's laptop.

Unlike a self-hosted cache, Cachely enforces read-only tokens at the API, so pull-request and fork builds can read but never write - closing the Nx cache-poisoning attack (CVE-2025-36852). It adds ROI reporting (the real build minutes and dollars the cache saved), per-tool insights, and build-optimization suggestions on top.

Pricing is a flat per-workspace subscription with no per-seat fees - add every developer, bot, and CI actor without watching the bill. Cachely never stores your source code; it caches only task outputs and their content hashes. Nx and Turborepo today; Bazel on the roadmap.

DataMelt

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

Cachely.dev

$ Details
freemium
Platforms
-
Release Date
2026 June

DataMelt features and specs

  • 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.

Cachely.dev features and specs

  • Simplified Caching Setup
    Cachely.dev likely offers an easy-to-integrate caching layer that reduces the complexity of manually configuring caching infrastructure, allowing developers to implement caching with minimal setup time.
  • Performance Improvement
    By providing a dedicated caching solution, Cachely.dev can help reduce latency and improve application response times, especially for frequently accessed data or API responses.
  • Developer-Focused Design
    The .dev domain and branding suggest the product is tailored specifically for developers, potentially offering clean APIs, SDKs, and documentation that fit into modern development workflows.
  • Scalability
    As a specialized caching service, it may be built to handle scaling automatically, removing the burden of managing cache infrastructure as traffic grows.
  • Reduced Backend Load
    Effective caching can significantly reduce the load on primary databases and backend services, potentially lowering infrastructure costs and improving overall system reliability.

Category Popularity

0-100% (relative to DataMelt and Cachely.dev)
Technical Computing
100 100%
0% 0
Productivity
0 0%
100% 100
Office & Productivity
100 100%
0% 0
Developer Tools
0 0%
100% 100

Questions & Answers

As answered by people managing DataMelt and Cachely.dev.

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

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Reviews

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

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

Cachely.dev Reviews

We have no reviews of Cachely.dev yet.
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What are some alternatives?

When comparing DataMelt and Cachely.dev, you can also consider the following products

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

nxCloud - nxCloud is a commercial OwnCloud provider

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

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.

Aveloy Graph - Aveloy Graph is an application for graph creation / data visualization

IGOR Pro - Technical graphing and data analysis for Macintosh and Windows.