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Top 10 Open Source Big Data Analytics Platforms

Big Data — is a pretty common concept in IT and digital marketing. Essentially, the definition is on the surface: the term “big data” implies managing and an analysis of big volumes of data. Broadly speaking, this is information which cannot be processed by classical approaches due to its volume.

  • Storage and transferring of the incoming information to gigabytes, terabytes and zettabytes for holding, processing and practical application.
  • Structuring of the scattered content: texts, images, video and audio files, and any other types of files.
  • Big Data analysis and the implementation of various approaches to processing of the scattered information and analytical reports generation.

Top 10 Open Source Big Data Platform:


Altamira Technologies | Full Spectrum Innovation. Altamira LUMIFY is a powerful big data fusion, analysis, and visualization platform that supports the development of actionable intelligence. Users discover complex connections and explore diverse relationships in their data through a suite of analytic options, including graph visualizations, full-text faceted search, dynamic histograms, interactive geospatial views, and collaborative workspaces shared in real-time. BEST!!!




MongoDB for GIANT Ideas – Build innovative modern applications that create a competitive advantage.. MongoDB is at the forefront of these two trends. As the world’s leading open source database with 10 million downloads and counting, MongoDB offers companies a faster, lower cost way to bring solutions to market. MongoDB provides the operational data store to handle the data that is created, stored, retrieved and analyzed by Big Data applications.




Talend Real-Time Open Source Big Data Integration Software. Talend open source integration software products offer real-time solutions for all types of data integration. Learn more about the benefits of Hadoop and Spark.




Infosys – Consulting | IT Services | Digital Transformation. What kind of relationship do you have with your data? Is it just a useful static resource that helps you understand what has been? Is it that living asset with the power to open up possibilities of the future? No matter what business you’re in, you too can turn structured and unstructured data into knowledge. Light up your path to innovation and growth in real-time and at a fraction of the cost.




AI for your business | CrowdFlower. The CrowdFlower human-in-the loop platform uses advanced quality control mechanisms and sophisticated job design tools to organize and streamline your big data.




Innovation in the big data space is extremely rapid, but combining multiple technologies into an end-to-end solution can be extremely complex and time-consuming. The vision of PNDA is to remove this complexity and allow you to focus on your solution. PNDA brings together a number of open source technologies to provide a simple, scalable big data analytics platform.




Cask – Big Data Applications on Hadoop. Cask Data Application Platform, CDAP, is the First Unified Integration Platform For Big Data that cuts down the time to production for data applications and Data Lakes by 80%. CDAP is a 100% open source platform that provides both data integration and app development capabilities on Apache Hadoop and Spark. The platform helps you future proof your big data investments, provides rapid time to value, and empowers your business users with a self-service user experience.




HPCC Systems. HPCC Systems is an open source, massive parallel-processing computing platform for big data processing and analytics.




KNIME | Open for Innovation. KNIME Analytics Platform is the leading open solution for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. Our enterprise-grade, open source platform is fast to deploy, easy to scale and intuitive to learn.




Arvados | Open Source Big Data Processing and Bioinformatics. The Arvados core is a platform for production data science with very large data sets. It is made up of two major systems and a number of related services and components including APIs, SDKs, and visual tools.



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