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Decoding Big Data Infrastructure Decisions:
Big data is playing an increasingly sign...
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Data in Motion vs Data at Rest

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In general, data can be broken into two categories – data in motion vs data at rest. Learn the difference between these two types of data and the best infrastructure options to get optimal performance.

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Data in Motion vs Data at Rest

  1. 1. Decoding Big Data Infrastructure Decisions: DATA AT REST DATA IN MOTIONvs SUMMARY Big data is playing an increasingly significant role in business success as organizations strive to generate, process and analyze massive amounts of information in order to make better business decisions. WORKLOAD REQUIREMENTS Viewing data through the lens of one of these two general categories – at rest or in motion – can help organizations determine the ideal data processing method and optimal infrastructure required to gain actionable insights and extract real value from big data. TWO CATEGORIES OF DATA Data in Motion Data at rest refers to information that has been collected from various sources and is analyzed after the data-creating events have occurred. The data analysis occurs separately and distinctly from any action taken on the conclusions of that analysis. A retailer analyzes a previous month’s sales data and then uses it to make strategic decisions about the present month’s business activities. The action takes place well after the data-creating event. The data scrutinized may spread amongst multiple collection points consisting of inventory, sale price, sales made, regions, and other pertinent information. These wristbands constantly record data about the guests’ activities. A theme park uses wristbands to collect data about their guests. The theme park is able to customize the guest experience in real time, during the visit. The collection process for data in motion is similar to that of data at rest; however, the difference lies in the analytics. In this case, the analytics occur in real-time as the event takes place. In general, data can be broken down into two basic categories – data at rest and data in motion – each with different infrastructure requirements based on availability, processing power and performance. The optimal type of infrastructure depends on the category and the business objectives for the data. DATA AT REST DATA IN MOTION Public Cloud Public cloud can be an ideal infrastructure choice in this scenario, from a cost standpoint, since virtual machines can easily be spun up as needed to analyze the data and spun down when finished. Bare-Metal Cloud DATA AT REST DATA IN MOTION For data in motion, a bare-metal cloud environment may be a preferable infrastructure choice. Bare-metal cloud involves the use of dedicated servers that offer cloud-like features without the use of virtualization. LAST MONTH 59% Fifty-nine percent of respondents to a recent Internap survey reported performance challenges associated with hosting big data applications in the cloud. vs TWO INFRASTRUCTURE OPTIONS Data at Rest To achieve optimal performance and cost efficiency, choose the right infrastructure to support the requirements of your big data workload. Bare Metal Edge Bare-metal technologies can enable the same self-service, on-demand scalability and pay-as-you go pricing as a traditional virtualized public cloud. Bare-metal cloud, however, eliminates the resource constraints of multi-tenancy, delivering the performance levels of dedicated servers, making it a better choice for processing large volumes of high-velocity data in real time. Public Cloud Misconception Until recently, many organizations may have assumed public cloud to be the natural choice for data in motion. However, as more companies host big data applications in the public cloud, they are confronting its performance limitations, particularly at scale. Batch Processing for Large Volumes Flexible, Self-provisioning Capabilities On-demand Scalability Real-time Analytics Dedicated, Always-on Infrastructure On-demand Scalability Tweet this InfographicSOURCES: INTERNAP CLOUD LANDSCAPE REPORT