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 internap.com