http://bit.ly/1wsAuRS - There are many hidden costs for Apache Hadoop that have different effects across different Hadoop distributions. With the new MapR TCO calculator organisations have a simple and reliable tool that is based on facts to compare costs.

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© 2015 MapR Technologies 1
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© 2015 MapR Technologies
Steve Wooledge, VP Product Marketing
Feb 18-20

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Top-Ranked NoSQL
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Goals of This Session
Insights to key factors for estimating
total cost of Hadoop ownership
Demo -
Online TCO Calculator for Hadoop
Help understand the differences in
Hadoop distros

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© 2015 MapR Technologies 5
Background – Why & How to Do TCO Analysis?
Operations teams need to forecast
size, staffing, and facility
requirements
There are many hidden costs for
Apache Hadoop
Not all Hadoop distributions are
created equally

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© 2015 MapR Technologies 6
Online TCO Calculator for Hadoop
Goals of online TCO calculator
– Simple and self-service
– Credible – detailed variables
– Educate on differences
based on FACTS
– Social and sharable
What it compares
– HDFS-based distributions vs. MapR Data Platform-based distribution

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© 2015 MapR Technologies 7
TCO Calculator for Hadoop
2 Total Hardware Costs
1 3-Year Total Cost of Ownership
4 Total Staffing Expenses
3
Environmentals
(Power, Space, Cooling)
Key Outputs for Customer
TB of data
# of files
% growth of data

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© 2015 MapR Technologies 8
Key Variables and Assumptions Taken Into Account
Hadoop FTE costs,
admin
$130k
per year
# of files /
NameNode
100M
Environmentals
(cost of electricity, rack
height, cost of floor space)
Discount rate on
money
10%
Data compression
ratios
3x
Software license/
support costs
$4k
per node
Cost and size of
hardware node
$9k
per node

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Demonstration – Online TCO Calculator

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Why the Differences in Cost?

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Hard Costs: Hardware + Environmentals
Architectural differences between MapR and HDFS-based distributions imply:
hardware required + maintenance, environmentals and labor costs

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Soft Costs: Labor
HDFS distros need more actual physical resources (servers) and more
resources to manage the complexity of HDFS-based system files. This implies:
staffing required with MapR

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Key Drivers of the MapR TCO Advantage
MapR No-NameNode Architecture
– HA without any special-purpose
hardware for NameNodes
– “Unlimited” file support greatly
reduces hardware
Automatic file compression
– MapR compresses 2-3x depending on
file type
– Reduces storage, but also reduced
network traffic and increases
performance
*Not reflected in the TCO model
Multi-tenancy*
– Fine-grained resource
management squeezes more
efficiency from hardware
– Reduces # of clusters for
multiple applications & groups
Higher performance*
– 2-7x higher throughput
– Less hardware for same
workload
1
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DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
No-NameNode Architecture
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
DataNode
NameNode
A B C D E FAAA BBBB CCC DDD EEE FFF
Up to 1T files (> 5000x advantage)
Significantly less hardware & OpEx
Higher performance
No special config to enable HA
Automatic failover & re-replication
Metadata is persisted to disk

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© 2015 MapR Technologies 17
MapR: Fast and Dependable Hadoop with Lowest TCO
Cost comparison for a 500 TB cluster vs HDFS-based distro’s
Online TCO Calculator for Hadoop: www.mapr.com/tco

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© 2015 MapR Technologies 18
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