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

$$$ $