Open Source Data Analytics Tools
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Data Analytics Tools
View 20 business solutionsBrowse free open source Data Analytics tools and projects for Windows and Linux below. Use the toggles on the left to filter open source Data Analytics tools by OS, license, language, programming language, and project status.
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Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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$300 Free Credits to Build on Google CloudPut 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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SciDAVis is a user-friendly data analysis and visualization program primarily aimed at high-quality plotting of scientific data. It strives to combine an intuitive, easy-to-use graphical user interface with powerful features such as Python scriptability.
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CyberChef
A web app for encryption, encoding, compression and data analysis
CyberChef, developed by GCHQ, is a versatile web application dubbed the "Cyber Swiss Army Knife." It enables users to perform a wide array of operations on data, including encryption, encoding, compression, and analysis, all within a browser interface. -
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Gephi
Gephi the open graph Viz platform
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks. Visualize networks up to a million elements. All actions (e.g. layout, filter, drag) run in real-time. Simple Easy to install and get started. An UI that is centered around the visualization. Like Photoshop™ for graphs. Modular Extend Gephi with plug-ins. The architecture is built on top of Apache Netbeans Platform and can be extended or reused easily through well-written APIs. -
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building block for doing practical, real world data analysis in Python, as well as powerful and flexible open source data analysis/ manipulation tool for any language. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++ Libraries for 15+ years and deployed it in millions of devices. Create software for connected embedded devices running Linux, Windows Embedded or QNX. Create cross-platform backends in C++ for iOS and Android applications and combine it with a native or HTML5-based user interface. Create software for IoT devices that talk to cloud backends over HTTP REST APIs. See macchina.io for an IoT platform built with POCO. -
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Bdash
Simple SQL Client for lightweight data analysis
Simple SQL Client for lightweight data analysis. You can share the result with gist. Supports MySQL, PostgreSQL (Amazon Redshift), SQLite3, Google BigQuery, Treasure Data, Amazon Athena. You can download and install from Web Site or Releases. -
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! When teaching data mining, we like to illustrate rather than only explain. -
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EEGLAB
EEGLAB is an open source signal processing environment
EEGLAB is an open source, MATLAB-based interactive environment for analyzing electrophysiological signals such as EEG and MEG. It incorporates powerful tools for data import, preprocessing, independent component analysis (ICA), time-frequency analysis, artifact rejection, and visualization—all within a GUI framework that also supports scripting and plugin extensions. EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command line only for Octave). This folder contains original Matlab functions from the EEGLAB (formerly ICA/EEG) Matlab toolbox, all released under the Gnu public license (see eeglablicence.txt). See the EEGLAB tutorial and reference paper (URLs given below) for more information. All distributed EEGLAB functions (admin, sigproc, pop, misc). -
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mrtg
MRTG - Multi Router Traffic Grapher
MRTG is a free, open-source tool designed to monitor and measure the traffic load on network links. It generates HTML pages containing graphical representations (PNG images) of network traffic, providing visual insights into bandwidth usage over time. Originally developed to monitor router traffic, MRTG has evolved to graph various network devices and other metrics. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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scikit-learn
Machine learning in Python
scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts. -
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DuckDB
DuckDB is an in-process SQL OLAP Database Management System
DuckDB is a high-performance analytical database system. It is designed to be fast, reliable and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to the Why DuckDB page on our website. Processing and storing tabular datasets, e.g. from CSV or Parquet files. Interactive data analysis, e.g. Joining & aggregate multiple large tables. Concurrent large changes, to multiple large tables, e.g. appending rows, adding/removing/updating columns. Large result set transfer to client. For development, DuckDB requires CMake, Python3 and a C++11 compliant compiler. Run make in the root directory to compile the sources. For development, use make debug to build a non-optimized debug version. -
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Apache InLong
Apache InLong - a one-stop integration framework for massive data
Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. InLong (应龙) is a divine beast in Chinese mythology who guides the river into the sea, and it is regarded as a metaphor of the InLong system for reporting data streams. InLong was originally built at Tencent, which has served online businesses for more than 8 years, to support massive data (data scale of more than 80 trillion pieces of data per day) reporting services in big data scenarios. The entire platform has integrated 5 modules: Ingestion, Convergence, Caching, Sorting, and Management, so that the business only needs to provide data sources, data service quality, data landing clusters and data landing formats. -
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StarRocks
StarRocks is a next-gen sub-second MPP database for full analytics
StarRocks is the next generation of real-time SQL engines for enterprise analytics. Real-time analytics is notoriously difficult. Complex data pipelines and de-normalized tables have always been a necessary evil. Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. From canceled orders to updated items, your analytics applications can easily handle them with StarRocks. From streaming data to change data capture, StarRocks meets the data ingestion demands of real-time analytics. Scale storage and computing power horizontally and support tens of thousands of concurrent users. All of your BI tools work with StarRocks through standard SQL. StarRocks provides superior performance. It is also a unified OLAP covering most data analytics scenarios. -
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awesome-single-cell
Community-curated list of software packages and data resources
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address the statistical challenges of single cell RNA-seq. The package incorporates novel and established methods to provide a flexible framework to perform filtering, quality control, normalization, dimension reduction, clustering, differential expression and a wide-range of plotting. An analytical framework for big-scale single cell data. Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction. -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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Datafor Visualization and Analysis
Visualization and Analysis
Datafor is a self-service agile BI tool that provides intuitive and user-friendly data visualization and analysis capabilities to help users quickly explore, analyze, and make decisions with their data. -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. Sweetviz integrates associations for numerical (Pearson's correlation), categorical (uncertainty coefficient) and categorical-numerical (correlation ratio) datatypes seamlessly, to provide maximum information for all data types. Automatically detects numerical, categorical and text features, with optional manual overrides. min/max/range, quartiles, mean, mode, standard deviation, sum, median absolute deviation, coefficient of variation, kurtosis, skewness. -
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Elasticsearch
A Distributed RESTful Search Engine
Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
JS Analyzer is a powerful static analysis tool implemented as a Burp Suite extension that helps security researchers and web developers automatically uncover important artifacts in JavaScript files during web application testing. It parses JavaScript responses intercepted by Burp Suite and intelligently extracts API endpoints, full URLs (including cloud storage links), secrets like API keys or tokens, and email addresses while filtering out noise from irrelevant code patterns. The extension is designed to reduce manual effort when analyzing large or obfuscated JavaScript assets, helping testers find security vulnerabilities and sensitive information faster and more reliably. It also includes UI features such as live search, result filtering, and the ability to export findings in JSON format for further processing. The underlying engine can be used independently in Python, enabling integration into custom workflows or automated pipelines outside Burp Suite. -
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AlphaPlot
Interactive scientific graphing and data analysis software.
Alpha Plot can generate different types of 2D and 3D plots (such as line, scatter, bar, pie, and surface plots) from data that is either imported from ASCII files, entered by hand, or calculated using formulas. The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). The GUI of the application uses the Qt toolkit. Periodic test builds are available here http://alphaplot.sourceforge.net/test-build.html -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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R packages (maintained by YJLEE)
R packages for PK/PD modeling , BE/BA, drug stability, ivivc, etc.
These R packages are developed for data analysis of PK/PD modeling & simulation, bioequivalence/bioavailability (BE/BA), drug stability, in-vitro and in-vivo correlation (ivivc), as well as therapeutic drug monitoring (TDM). -
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FlowViewer
FlowViewer is a web-based netflow data analysis tool.
FlowViewer provides a convenient web-based user interface to Mark Fullmer’s flow-tools suite and CMU's netflow data capture/analyzer, SiLK. The inclusion of the underlying SiLK tool set enables FlowViewer users to continue to use the tool with the newer IPFIX netflow data protocol, which includes support for IPv6 and Cisco's v9 and FNF netflow. FlowViewer has been developed for NASA’s Earth Sciences Data and Information System (ESDIS) networks, and credit goes to NASA for their usual outstanding support of innovation. The FlowViewer tools provide additional graphing and tracking features by utilizing open source software including Thomas Boutrell’s gd, Lincoln Stein's GD, Martien Verbruggen's GD::Graph, and Tobias Oetiker’s RRDtool. FlowViewer v4.6 fixes non-UTC local time environments for FlowViewer and FlowGrapher, and $no_devices_or_exporters FlowMonitor_Collector problem. **Note: SiLK must be v3.8.0 or later. Version 3.9 handles sFlow data. -
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CloudQuery
The open-source cloud asset inventory powered by SQL
CloudQuery extracts, transforms and loads your cloud assets into normalized PostgreSQL tables. CloudQuery enables you to assess, audit, and monitor the configurations of your cloud assets. Use standard SQL to find any asset based on any configuration or relation to other assets. Connect CloudQuery standard PostgreSQL database to your favorite BI/Visualization tool such as Grafana, QuickSight, etc. Codify your security & compliance rules with SQL as the query engine. Integrate CloudQuery with your current visualization, monitoring, and alerting such as Grafana. CloudQuery supports the TimescaleDB PostgreSQL extension, giving you full historical snapshots of your cloud asset inventory. Data analysis, security, auditing, and compliance. Leverage SQL to get visibility into your cloud infrastructure and SaaS applications. Build a cloud-asset inventory across any of our supported official or community providers.
