Software Alternatives, Accelerators & Startups

DataMelt VS LinearB

Compare DataMelt VS LinearB and see what are their differences

DataMelt logo DataMelt

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

LinearB logo LinearB

LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
  • 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

  • LinearB Landing page
    Landing page //
    2023-08-19

DataMelt

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

LinearB features and specs

  • Integration with Existing Tools
    LinearB integrates seamlessly with popular project management and communication tools like Jira, GitHub, Slack, and Bitbucket, making it easier to adopt without changing the existing workflow.
  • Real-time Metrics
    Provides real-time visibility into the software development lifecycle, allowing teams to gain insights and take immediate action to improve development processes.
  • Automated Analytics
    Automates the collection and analysis of data, reducing the manual effort required to gather metrics and allowing teams to focus on decision-making and improvements.
  • Workflow Optimization
    Offers features to identify bottlenecks and inefficiencies in the development process, enabling teams to streamline workflows and improve productivity.
  • Developer Metrics
    Includes metrics specifically for developers, such as code quality scores, pull request review times, and activity reports, to help individual contributors understand and enhance their performance.

Possible disadvantages of LinearB

  • Learning Curve
    Although the tool integrates well with other platforms, there is a learning curve associated with understanding and utilizing all of its features effectively.
  • Potential Overload of Metrics
    The extensive array of metrics and data presented can be overwhelming for teams not accustomed to such detailed analytics, potentially causing decision paralysis.
  • Cost
    The pricing structure might be expensive for small teams or startups, especially when compared to other simpler project management or analytics tools.
  • Dependency on Data Integration
    The effectiveness of LinearB largely depends on the quality and comprehensiveness of the data integrated from other tools. Inconsistent or incomplete data can hamper its utility.
  • Privacy Concerns
    Given the level of detail and access required, there might be concerns around data privacy and the handling of sensitive project information, especially in heavily regulated industries.

Analysis of LinearB

Overall verdict

  • LinearB is generally considered a good tool for teams looking to improve their development workflows. It receives positive feedback for its ability to provide actionable insights and its user-friendly interface. However, as with any tool, its effectiveness can vary depending on the specific needs and context of the development team.

Why this product is good

  • LinearB is a tool that provides real-time insights into software development processes. It enhances productivity by offering metrics, workflow automation, and project visibility, which help in making data-driven decisions. The platform is designed to streamline development pipelines, ensuring teams can identify bottlenecks quickly and optimize their work processes.

Recommended for

    LinearB is recommended for software development teams, engineering managers, and project managers who want to improve visibility into their development processes, reduce cycle times, and boost overall productivity. It's particularly useful for teams that rely on agile methodologies and need to continuously monitor and improve their workflow efficiency.

Category Popularity

0-100% (relative to DataMelt and LinearB)
Technical Computing
100 100%
0% 0
Data Dashboard
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 LinearB.

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 LinearB

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

LinearB Reviews

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

Social recommendations and mentions

Based on our record, LinearB seems to be more popular. It has been mentiond 28 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.

LinearB mentions (28)

  • The top 15 developer productivity tools in 2026
    LinearB is an engineering productivity platform that provides visibility into developer workflows, automation, and process metrics. It collects data across the entire development lifecycle to diagnose blockers and optimize delivery. One user reports saving 321 developer-hours per month. - Source: dev.to / 3 months ago
  • Developer Productivity vs Developer Experience: Why You Can't Fix One Without the Other
    Most tools measure half the picture. Traditional metrics platforms like LinearB focus on quantitative signals (DORA metrics, cycle time). Survey platforms like Culture Amp capture sentiment across organizations but aren't developer-specific. DX (founded by DORA/SPACE research creators) combines developer surveys with SDLC analytics. These approaches require deliberate implementation and buy-in. - Source: dev.to / 8 months ago
  • ๐ŸฆŠ GitLab: A Python Script Calculating DORA Metrics
    LinearB is a SaaS solution that retrieves metrics overtime, some of them being used to calculate DORA Metrics. They also have a Youtube channel that advocate for DORA Metrics and more. - Source: dev.to / over 2 years ago
  • 6 Proven Strategies For Being A Great Platform Engineer
    In helping engineering orgs get visibility into developer workflows with LinearB, Dan Lines and Ori Keren discovered that the majority of cycle time was being spent in pull request and code review. They found that:. - Source: dev.to / about 3 years ago
  • How to consolidate metrics from across the entire organisation
    LinearB and there are a few cheaper alternatives. Ties in DORA metrics from gut repos and agile project management tools like JIRA. https://linearb.io. Source: about 3 years ago
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What are some alternatives?

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

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

Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.

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

Swarmia - Swarmia is an engineering productivity software trusted by 600+ engineering teams worldwide. Use key engineering metrics to unblock the flow, align engineering with business objectives, and drive continuous improvement.

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.

CodeClimate - Code Climate provides automated code review for your apps, letting you fix quality and security issues before they hit production. We check every commit, branch and pull request for changes in quality and potential vulnerabilities.