Conclusion
99.99%decrease in cost of storage
From RDBMS to MongoDBThe Evolution of the Modern Database
The Increasing Three V’s of DataVelocity, Variety, and Volume
The Decreasing Storage costCost per 1GB of storage
90%of data isunstructured (IDC)
This very second as you are reading this infographic, data is
being collected from all around the world. Organizations that have
depended solely on relational databases are now focusing on
modernizing their databases; adjusting to the changes.
With massive amounts of data flowing in from multiple sources,
modern databases are evolving to improve their capacity, speed,
and accuracy.
NowModern Database
ThenRelational Database
C1 C2 C3 C4 C5
So, how well can MongoDB handle all this data?
How can this financially benefit my business?
How can this financially benefit my business?
But wouldn’t all this be so costly?
The Increasing cost of Development ResourcesInfrastructure vs. Developer cost
But developers are so expensive to hire....
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2009
Worldwide Enterprise Data Growth
20142004
Unstructured data
Structured data
Data growing at
40%annually. (IDC)
MetLife tried to consolidate 70 legacy systems into a single
record for years. The project had no end in sight.
Problem
MetLife’s 360 degree view of their customers, the Wall, now
allows them to minimize churn by improving customer service.
Conclusion
$437,0001980’s
$0.052014
$ $ $ $
$ $ $ $
$ $ $ $
$ $ $ $
$ $ $ $
$ $ $ $
¢
99.99% decrease in storage cost
MongoDB’s dynamic schema and ease of use increases
developer productivity and improves time to market by 5x to 10x.
Shutterfly’s hardware costs remained high with their
RDBMS implementation, features took too long to build and
site performance suffered.
Problem
Shutterfly was able to take advantage of commodity
infrastructure to cut costs and improve performance.
Conclusion
SolutionWith MongoDB
Telefonica tried to build a personalization server for millions
of user profiles with 20 technologists for 15 months, but
failed to meet new performance requirements.
Problem
Telefonica joins the long list of companies building
applications better and faster with MongoDB.
Conclusion
SolutionWith MongoDB 3.5 moImplementation took 1/4 of thetime it originally took.
10 devsTelefonica was able to build a new version with half the number of developers they startedoff with.
80%Costs invested in data storage was reduced by 80% by scaling out on commodity servers.
9xShutterfly were able to increase its performance 9 times better.
SolutionWith MongoDB 90 daysIt took only a few months to take their app into production.
2 weeksMetLife built an app protype in just 14 days.
1985 2014
Developer cost Infrastructure cost
Let’s see the break down of modern data
x10
$$$ $
