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Squey is designed from the ground up to take advantage of GPUs and CPUs to perform interactive explorations of massive amounts of data. It gives users an exhaustive yet intuitive multi-view representation of columnar data and can ingest from: 1. Structured text files (CSV, logs, ...) 2. Apache Parquet files 3. Pcap files 4. SQL databases 5. Elasticsearch databases Squey strives to deliver value through its V.I.SU approach: - Visualize: Leverage various visual representations of raw data in combination with statistics - Investigate: Use filters to build an accurate understanding of millions of rows while switching instantly between capturing the big picture and focusing on the details - Spot the Unknown: As a structured understanding of the data emerges, identify unknowns and anomalies Squey can be used for many different purposes, such as: - BI and Big Data: Bootstrap initial understanding of complex datasets and deep dive where necessary to design accurate data processing - Cybersecurity: Detect weak signals such as attacks and data leaks - IT troubleshooting: Resolve network issues and improve application performance - Machine Learning: Design training dataset to fulfill targeted improvements of Machine Learning models Give yourself a chance to see your data and have fun exploring!

Tags visualization data-visualization data-analysis cybersecurity parallel-coordinates timeseries parquet pcap
License MITL
State stable

Recent Releases

Latest14 Oct 2024 09:58 minor feature: https://gitlab.com/squey/squey/-/raw/main/CHANGELOG