Browse free open source Big Data tools and projects below. Use the toggles on the left to filter open source Big Data tools by OS, license, language, programming language, and project status.

  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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  • Paessler - Monitor Your Whole Network in Minutes Icon
    Paessler - Monitor Your Whole Network in Minutes

    Auto-discovery finds your devices and deploys pre-configured sensors instantly. No project plan required, just visibility from day one.

    Waiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
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  • 1
    qvge

    qvge

    Qt Visual Graph Editor

    qvge is a multiplatform graph editor written in C++/Qt. Its main goal is to make possible visually edit two-dimensional graphs in a simple and intuitive way. Please note that qvge is not a replacement for such a software like Gephi, Graphvis, Dot, yEd, Dia and so on. It is neither a tool for "big data analysis" nor a math application. It is really just a simple graph editor :)
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2
    Sample Level Musical Timeline

    Sample Level Musical Timeline

    Sample Level Modulation of Musical Timeline

    Sample Level Modulation of Musical Timeline Mingfeng Zhang Dept. of Electrical and Computer Engineering, University of Rochester In this toolbox we provide signal processing tools to allocate music events (samples of musical notes) to specified time locations with sample level accuracy. In this implementation, we use computational tools to add in micro-timing variations in J.S. Bach four-part chorales as a "visualizer" for big data. By extracting data patterns from multiple time scales, we implement a tool that musicians can perform the big data at different resolutions. This toolbox will need the following supporting toolboxes: MIDI TOOLBOX https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/miditoolbox MIR TOOLBOX https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/mirtoolbox Please add the path in MATLAB for these two toolbox. Please also read the project document file (readme.doc/pdf) for more details
    Downloads: 0 This Week
    Last Update:
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