About

See presentation video : https://www.youtube.com/watch?v=M9I8Vt5mmAc

Project description

<!-- project_description_start --> <p><a href="https://squey.org">Squey</a> is designed from the ground up to take advantage of GPUs and CPUs to perform interactive explorations of massive amounts of data.</p> <p>It gives users an exhaustive yet intuitive multi-view representation of columnar data and can ingest from:</p> <ol> <li>Structured text files (CSV, logs, ...)</li> <li>Apache Parquet files</li> <li>Pcap files</li> <li>SQL databases</li> <li>Elasticsearch databases</li> </ol> <p>Squey strives to deliver value through its <b>V.I.SU</b> approach:</p> <ul> <li><b>Visualize</b>: Leverage various visual representations of raw data in combination with statistics</li> <li><b>Investigate</b>: Use filters to build an accurate understanding of millions of rows while switching instantly between capturing the big picture and focusing on the details</li> <li><b>Spot the Unknown</b>: As a structured understanding of the data emerges, identify unknowns and anomalies</li> </ul> <p>Squey can be used for many different purposes, such as:</p> <ul> <li><b>BI and Big Data</b>: Bootstrap initial understanding of complex datasets and deep dive where necessary to design accurate data processing</li> <li><b>Cybersecurity</b>: Detect weak signals such as attacks and data leaks</li> <li><b>IT troubleshooting</b>: Resolve network issues and improve application performance</li> <li><b>Machine Learning</b>: Design training dataset to fulfill targeted improvements of Machine Learning models</li> </ul> <br> <p>Give yourself a chance to <b>see</b> your data and have fun exploring!</p> <!-- project_description_end -->

Installation

Windows

<a href="https://apps.microsoft.com/detail/9PDP9BKD9NVD?mode=full"> <img src="https://get.microsoft.com/images/en-us%20dark.svg" width="200" alt="Download from the Microsoft Store" style="border: 1px solid #bbbbbb; border-radius: 10px;"/> </a> <br/>

Or install it using a standalone archive.

macOS

<a href="https://apps.apple.com/app/squey/id6748079336"> <img src="https://toolbox.marketingtools.apple.com/api/v2/badges/download-on-the-app-store/black/en-us?releaseDate=1647734400" width="200" alt="Download on the App Store"/> </a> <br/>

Or install it using Apple silicon (arm64) or Intel (x86_64) disk image.

Linux

<a href="https://flathub.org/apps/details/org.squey.Squey"> <img width='200' alt='Get it on Flathub' src='https://flathub.org/api/badge?locale=en'/> </a> <br/>

flatpak install --user -y https://dl.flathub.org/repo/appstream/org.squey.Squey.flatpakref
flatpak run org.squey.Squey

AWS

Deploying the software as a service on an AWS EC2 instance :

<img src="https://squey.org/images/logos/aws_marketplace.png" width="200"/>

Reference manual

https://doc.squey.org

Development

See the developement README.md page.

Installing a development branch

Note : Merge Requests having the export_linux_package label are exported by the CI/CD pipeline as a flatpak package named after the git branch name.

Adding the flatpak development remote (once):

flatpak --user remote-add --no-gpg-verify squey_dev http://inspector-cassiopee.ensam.eu/flatpak

Installing a development branch:

flatpak install --user squey_dev org.squey.Squey//<dev_branch_name>

export_windows_package and export_macos_package can also be used to generate the packages targeting these platforms.

Roadmap

https://gitlab.com/groups/squey/-/roadmap

Support the project

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Help the contributors to develop and maintain the software