Measured in terms of volume, velocity, and variety, big data has become a major disruption in the business intelligence and data management industry. With traditional solutions becoming too expensive to scale or adapt to rapidly evolving conditions, companies are looking to find affordable solutions that will help them store, process, and query all of their data.

bigdata

InetServices has been proving custom big data solutions for the past several years.  Seeing the huge increase in demand, we have created three standard configurations to make it easier for companies to order extreme computing power on demand.

Big Data Configurations:

Product                 Cores                    RAM      SSD Storage        Monthly

Big.Data.1            24 cores               96GB     720GB SSD          $796/mo

Big.Data.2            32 cores               128GB   1200GB SSD        $1086/mo

Big.Data.3            40 cores               256GB   1920GB SSD        $1723/mo

 

NOTE:
Built entirely with RAID protected, data-center-grade SSDs
Powered with the latest Intel® Xeon® processors
10 Gigabits per second network throughput between every host machine

Big data defined

Volume. Many factors contribute to the increase in data volume. Transaction-based data stored through the years. Unstructured data streaming in from social media. Increasing amounts of sensor and machine-to-machine data being collected. In the past, excessive data volume was a storage issue. But with decreasing storage costs, other issues emerge, including how to determine relevance within large data volumes and how to use analytics to create value from relevant data.

Velocity. Data is streaming in at unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time. Reacting quickly enough to deal with data velocity is a challenge for most organizations.

Variety. Data today comes in all types of formats. Structured, numeric data in traditional databases. Information created from line-of-business applications. Unstructured text documents, email, video, audio, stock ticker data and financial transactions. Managing, merging and governing different varieties of data is something many organizations still grapple with.

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