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.

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    MOA - Massive Online Analysis

    MOA - Massive Online Analysis

    Big Data Stream Analytics Framework.

    A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.
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    Downloads: 175 This Week
    Last Update:
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  • 2
    Vespa

    Vespa

    The open big data serving engine

    Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information.
    Downloads: 25 This Week
    Last Update:
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  • 3
    Flamingo Project

    Flamingo Project

    Workflow Designer, Hive Editor, Pig Editor, File System Browser

    Flamingo is a open-source Big Data Platform that combine a Ajax Rich Web Interface + Workflow Engine + Workflow Designer + MapReduce + Hive Editor + Pig Editor. 1. Easy Tool for big data 2. Use comfortable in Hadoop EcoSystem projects 3. Based GPL V3 License Supporting Pig IDE, Hive IDE, HDFS Browser, Scheduler, Hadoop Job Monitoring, Workflow Engine, Workflow Designer, MapReduce.
    Downloads: 15 This Week
    Last Update:
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  • 4
    Parkiet

    Parkiet

    Parquet format file GUI editor

    Parquet file viewer and editor written in Java and SWT. It uses Apache Avro library for reading and writing edited parquet files. Only Parquet files with simple data type columns are supported.
    Downloads: 1 This Week
    Last Update:
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  • 5

    Faum

    Fast Autonomous Unsupervised Multidimiensional Classification

    This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful.
    Downloads: 1 This Week
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  • 6
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    .NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.
    Downloads: 0 This Week
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  • 7

    Chordalysis

    Log-linear analysis (data modelling) for high-dimensional data

    ===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures, also known as chordal graphs. Chordalysis makes it possible to discover the structure of datasets with thousands of variables on a standard desktop computer. Associated papers at ICDM 2013, ICDM 2014 and SDM 2015 can be found at http://www.francois-petitjean.com/Research/ YourKit is supporting Chordalysis open source project with its full-featured Java Profiler. YourKit is the creator of innovative and intelligent tools for profiling Java and .NET applications. http://www.yourkit.com
    Downloads: 0 This Week
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  • 8
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling. DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses.
    Downloads: 0 This Week
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  • 9
    FinMind

    FinMind

    Open Data, more than 50 financial data

    In the era of big data, data is the foundation of everything. We collect more than 50 kinds of Taiwan stock related information and provide download, online analysis, and backtesting. Regardless of the program, you can download data through the api provided by FinMind, or you can download data directly from the website. After data is available, statistical analysis, regression analysis, time series analysis, machine learning, and deep learning can be performed. For individual stocks, provide visual analysis of technical, fundamental, and chip levels. According to different strategies, back-test analysis is performed to provide performance, profit and loss, and stock selection targets of different strategy investment portfolios.
    Downloads: 0 This Week
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  • 10
    HPCC Systems

    HPCC Systems

    End-to-end big data in a massively scalable supercomputing platform.

    Important: As of April 20, 2026, this project can now be found at https://github.com/hpcc-systems/HPCC-Platform/releases. HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and decisions. HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single, complete end-to-end architecture for efficient processing.
    Downloads: 0 This Week
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  • 11

    PanoramaServer

    Open Source Panorama Server for free virtual tour of 360 degrees views

    Ideal for creating virtual tours of panoramic views for all sorts including property exhibition for brokers at real estate agencies/property agents, tour guide for indoor/outdoor venues, information to public/private facilities for curators, travel journal for tourist as log book, backdrop setting for storytelling, treasure hunt like games, big data mining for pattern through computer vision in artificial intelligence, etc. It is like creating your own Google Map Street View. All is required by the user is to have photos of equirectangular format (panorama) taken from 3D cameras common for on-site premises. These images can be referenced by the PanoramaServer to create virtual travels with 360 degrees view where viewers can navigate to different locations, view information, etc. If made available online to general public over the internet, can even share the link of your virtual trips. PanoramaServer is free as it is open source licensed.
    Downloads: 0 This Week
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  • 12
    SentimentAnalysis-Rick&Morty

    SentimentAnalysis-Rick&Morty

    Rick & Morty Sentiment Analysis - End-of-Degree Project - UNIR

    The remarkable progress in the field of Big Data has driven the development of new technologies in natural language processing and data analysis. Text mining is a fascinating application of data analysis that extracts relevant information from related writings in different linguistic contexts. And therefore, in natural language processing, sentiment analysis and classification stands out as a key application supported by text mining. Through the extraction of information from textual data, it becomes possible to identify and comprehend the sentiments and emotions conveyed. In this end-of-degree work, we analyze and classify the dialogue of characters in an English-language television series as "Rick and Morty" using Python. The objective is to identify and categorize the feelings and emotions expressed in the text, comparing the human perception of the characters' personalities with the results obtained using natural language processing techniques.
    Downloads: 0 This Week
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  • 13
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots, make working with data feel refreshingly fast, futuristic, and intuitive. Version with git, run as Python scripts, import symbols from a notebook into other notebooks or Python files, and lint or format with your favorite tools. You'll always be able to reproduce your collaborators' results. Notebooks are executed in a deterministic order, with no hidden state, delete a cell and marimo deletes its variables while updating affected cells.
    Downloads: 0 This Week
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