Going Green With Data Warehouse Appliances
Businesses are seeking ways to support green environments and sustainable
energy programs. IT can make more significant contributions to such
initiatives as vendors roll out energy program supporting hardware.
Recently, Terradata announced the combination of machines
Findings from a survey of IT professionals conducted by ONStor,
a provider of NAS solutions, and reported by DM Direct in March
- At their current data growth rate, 43 percent can only retain
current performance in their current infrastructure for only 6
- 12 months
- 24 percent reported that the most serious issue driving the
reduction of data infrastructure power consumption is the cost
and time of building another data center.
According to Gartner IT, the top strategic technology for 2008 is
Green IT, based on the significant difference implementing Green
IT will make in an organization’s work. Further, not doing
so carries a competitive risk.
Green IT is impacting how IT groups budget and implement technology,
based on challenging preconceived ideas around the physical attributes
of the data center.
Green Solutions To Data
So how does a data center reconcile the challenging growth of data
with shrinking physical resources.
Data Warehouse Appliances
One solution suggested is the data warehouse appliance [DWA].
The DWA combines processing and storage in one unit to address challenges
of working with big data. It is economical in space requirements
and extremely efficient in processing capacity. More on data warehouse
Hardware vendors now provide energy usage data for each of their
products. For instance, Dell publishrd lab test results of their
PowerEdge server for energy-conscious buyers to gain a detailed
picture of power consumption.
Cooling is one of the largest power users - HP’s Liquid Cooling
technology, fans, venting and physical placement of components all
reduce the thermal output or the power required to dissipate heat.
Less attention is paid to physical size and the impact it has on
a machine’s greenness but size does matter when calculating
the cost of floor space and new construction.
Together, ower consumption, thermal output and physical size establish
a machine’s environmental footprint. Using density computations,
the environmental cost of processing requirements can be quantified.
In a data warehousing environment, computing density is calculated
per terabyte of data.
Typically, DWAs [by combining server and storage] offer energy
- Eliminating the redundancy that results from having servers
dedicated to data processing and servers dedicated to data storage.
There are generally fewer CPUs in play, fewer fans, etc.
- Reducing load on network infrastructure as they process data
near the point of storage. Moving data around the network uses
large amounts of power. Communications equipment has the highest
rate of energy consumption per square foot. Switches and fibre
channel alone can account for 14 percent of a data center’s
energy consumption.3 Some DWAs use fibre channel for inter-node
or inter-appliance communication, however even they are conservative
consumers compared to SAN storage devices.
- Implementing Massively Parallel Processing (MPP) spreads work
across CPUs and disks in such a way that lessens redundant spin
or idle cycles.
In addition to these efficiencies that are inherent in the appliance
form factor, there are other techniques that vendors can use to
further conserve energy, for example, selecting high-efficiency
processors. AMD’s HE Opteron processors use 58 percent (95
watts cf. 55 watts for HE processors) of what their “standard”
processors use. SATA drives and Flash memory, as well as more
energy efficient RAID controllers and switches can contribute
Computing Density = (Power + Cooling) x
Less Power Usage = less thermal ouput = less
cooling = less power usage.
The cooling factor is an output of the power and space - it takes
as much energy to cool a device as it does to power the device.
Many energy consumption specs do not account for the cooling part
of the equation.
Costs of cooling the data center include both internal equipment
cooling as well as the cost of targeted ducts or vents.
In calculating the data center’s share of total resource usage,
calculations must include both the power used by hardware and that
used for ambient and supplemental cooling.
The table below illustrates the watt hours consumed by two physical
data warehouse architectures under an average processing load: a
host server for the DBMS with a storage server with 1.5TB capacity
and a DWA with 2TB capacity.
|Server + SAN 1.5TB
||600 + Host DB Server Usage
Watt Hours Comparison
The difference is significant and underscores the advantages that
can be gained from using devices that have been engineered for specific
Larger machines require more space; more space costs more money
and has a larger ecological impact.
The efficient space usage of a DWA also contributes to a lower
energy consumption; a single appliance as opposed to two pieces
of independent hardware eliminates redundancy and is more compact.
The DWA offers both a smaller configuration as well as unique engineering
to provide massive capacity within the smaller footprint. This is
common to all DWAs.
Some DWAs combine third-party hardware preconfigured with specialized
software. Whilst still very energy-efficient, the general general-purpose
hardware used by these DWAs means their physical footprints end
up similar to that of a nonappliance server-and-storage stack.
Comparison of Environmental Footprints and Data Capacity
|DB Server + SAN Storage
For 2TB of data, a DWA’s environmental footprint is approximately
40 percent that of a server+SAN architecture. That ratio holds steady
even as the data warehouse expands in volume.
Hardware [storage arrays, servers and networking equipment] accounts
for 50 percent of the power requirements in the data center.
Energy-efficiency initiatives must focus at significantly reducing
hardware. This is where virtualization
technology is providing great savings. Energy efficiency and
space requirements are now among the primary selection criteria
for any new acquisition.
Teradata 5500 Server
Designed specifically for data warehousing, the high-availability
Teradata 5500 server
scales from hundreds of gigabytes to four petabytes. It provides
the capability to support rapid expansion in data volumes, heavier
decision-support demands and complex mixed workloads including deep
The dual-core Intel Xeon  chip set is much more efficient
at data warehouse workloads, compared to the Intel Itanium chip.
The Teradata 5500 server is a great example of improved carbon
footprint over each of these three domains:
Power Usage - The Teradata 5500 Server uses 75
percent less energy for the same capability data warehouse compared
to Teradata servers 3-5 years ago, according to Noel Pettitt, Teradata's
general manager for Australia and New Zealand. That represents the
typical power usage [kilowatt-hours] of 60 homes for a year!
Space - The 5500 Server requires approximately
66 percent less floor space.
Cooling - an improved cabinet design is said to
increase cooling efficiency.
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