EMC launches large data cloud analysis system for low cost and efficient work

Source: Internet
Author: User
Keywords Implementation work large data
Tags analysis cloud cloud analysis clouds company computing control cost

October 14 News, according to foreign media reports, EMC launched the use of large-scale parallel processing framework of the Integrated Data Warehouse system Greenplum the information Computing appliance.
  
This customized integrated database, operation, storage, and network system shipped after EMC acquired Greenplum to enable the analysis of large data clouds.
  
According to the company, this analytical capability is important for effective analysis of storage, management, fast retrieval, and space control of detailed data. These data can be from networks, surveillance systems, and sensors.
  
Scottmcnealy, Senior Consultant at the EMC Data Computing division, unveiled the application positioning of EMC products as a major infrastructure supplier with large and small customers to improve the company's Intelligent Analytics services. He said Greenplum introduced the next generation of data analysis technology to enable users to achieve data monetization services. The big Data age is coming.
  
The product uses the Greenplum Database 4.0, its large-scale parallel processing framework to achieve 10TB per hour download volume, and achieve lighter stability. Better than the competitor's products.
  
EMC says it is twice times faster than Oracle's Exadata, five times times faster than Netezza and Teradata, and can achieve low-cost and efficient work.
  
The system provides a half rack, a full rack and a multiple rack application architecture. and integrate EMC's replication, backup, recovery, and data deduplication technologies. Quocirca, the service director of the Clivelongbottom, says that as data volumes continue to grow, many companies are struggling to cope with massive data processing.
  
Many vendors have done data marts, data cubes, storage databases, and so on, all to deal with growing data.

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