|
Home | Technology News Search Engine:
|
|
|
|
Home: Technology News:
|
|
|
(IT-NEWSWIRE.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.
Whipsmart Market Intelligence blog
Whipsmart Market Intelligence Press Releases
Whipsmart
Neeraj
5102005090
neeraj@whipsmartmi.com
Source: EmailWire.Com 
Source: EmailWire.com
|
|
|
|
|
Technology News Headlines
|
|
|
|
|
Technology Business Video Feed
|
|
More Technology Video Feeds
|
|
|
