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  • WhipsmartMI 2021 Global GPU database Industry Research Report

    (I-SoftwareNews.Com, August 26, 2021 ) GPU databases can handle huge quantities of data more quicker and more effectively than CPU databases because they operate in parallel rather than in sequence. GPUs accelerate location-based and in-memory analytics, machine learning, and artificial intelligence (AI). With thousands of processing cores readily accessible on a single card, it is feasible to execute tasks in parallel, using brute force to solve complicated analytical processes that are difficult for conventional databases to handle. Aggregations, sorts, and grouping operations are time-consuming activities for a CPU, but they may be performed efficiently in parallel on a GPU database.



    High performance computing is becoming more important as data quantities continue to grow, as does the requirement to execute programmes as effectively as possible with these amounts of data. In order to do basic computations in parallel, CPUs are not suitable for deep learning tasks since they need a large number of cores, which are sometimes prohibitively expensive. As a cost-effective solution to the problem of parallel computing, graphics processing units (GPUs) are in great demand. The need for cyber security, fraud detection, and real-time data analytics, among other reasons, are also contributing to the expansion of this industry. GPU databases make it simple to deal with big or very rapid data sets that are produced from sources such as the Internet of Things (IoT) and commercial transactions. Processing complicated queries is made easier by the GPU's powerful computational capabilities.



    View more @ https://whipsmartmi.com/report/gpu-database-market



    Request a Sample of this report valued at USD 1500 (Single User License) @ https://whipsmartmi.com/sample/ic0770/GPU-database-Market



    This GPU database report offers the major market player’s profiles, such as Kinetica (US), OmniSci (US), SQream (US), Neo4j (US), NVIDIA (US), Brytlyt (UK), Blazegraph (US), BlazingDB (US), Zilliz (China), Jedox (Germany), HeteroDB (Japan), H2O.ai (US), FASTDATA.io (US), Fuzzy Logix (US), Anaconda (US), and Graphistry (US).



    The GPU database Market report has been categorized as below:



    Based on applications

    GRC

    Threat Intelligence



    CEM



    Fraud Detection and Prevention



    Predictive Maintenance



    SCM



    Others



    Based on components

    Tools

    GPU-accelerated Databases



    GPU-accelerated Analytics



    Services



    Based on deployment

    On-premises

    Cloud



    Based on verticals

    BFSI

    Retail and eCommerce



    Healthcare and Pharmaceuticals



    Telecommunications and IT



    Transportation and Logistics



    Government and Defense



    Others



    By Region



    North America

    Europe

    Asia Pacific

    Rest of World



    About whipsmartmi:



    We are a growth partnership company that provides fact-based consulting services focused on helping our clients achieve incremental and transformational growth competing in business-to- business and business-to- consumer markets. We facilitate their growth journey through an environment that is dominated by accelerating change, constant evolution of new business models, disruptive trends and technologies in their respective industry.



    We serve a wide spectrum of global industries such as Semiconductor and Electronics, Information Technology, Communication, Medical Devices, Pharmaceuticals, Defense, Aviation, and Chemicals among others. Our well-seasoned blend of technical and marketing expertise enables us to serve our customers with comprehensive study of global supply chains that helps them to devise highly effective strategies.



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