Your Data Has Changed • 90% of the world’s data was created in the last two years • 80% of enterprise data is unstructured • Unstructured data growing 2x faster than structured
You’re Not Alone What are the primary data issues driving you to consider Big Data?* *
From
Big
Data
Executive
Summary
of
50+
execs
from
F100,
gov
orgs “Of
Gartner's
"3Vs"
of
big
data
(volume,
velocity,
variety),
the
variety
of
data
sources
is
seen
by
our
clients
as
both
the
greatest
challenge
and
the
greatest
opportunity.”
-‐
Forrester,
2014 Diverse, streaming or new data types Greater than 100TB Less than 100TB
Data Types
Unstructured data
Semi-structured data
Polymorphic data
Agile Development
Iterative
Short development cycles
New workloads Relational Database Challenges Volume of Data
Petabytes of data
Trillions of records
Millions of queries/sec
New Architectures
Horizontal scaling
Commodity servers
Cloud computing
No SQL But Still Flexible Querying MongoDB {
first_name: ‘Paul’,
surname: ‘Miller’,
city: ‘London’,
location: [45.123,47.232],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
}
} Rich Queries Find Paul’s cars
Find everybody in London with a car built between 1970 and 1980 Geospatial Find all of the car owners within 5km of Trafalgar Sq. Text Search Find all the cars described as having leather seats Aggregation Calculate the average value of Paul’s car collection Map Reduce What is the ownership pattern of colors by geography over time? (is purple trending up in China?)
What We Sell MongoDB Enterprise Advanced
The best way to run MongoDB in your data center
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The easiest way to run MongoDB in the cloud.
Production Support
In production and under control
Development Support
Let’s get you running.
Consulting
We solve problems.
Training
Get your teams up to speed.
THE LARGEST ECOSYSTEM 9,000,000+ MongoDB Downloads 250,000+ Online Education Registrants 35,000+ MongoDB User Group Members 40,000+ MongoDB Management Service (MMS) Users 750+ Technology and Services Partners 2,000+ Customers Across All Industries
Single View of Customer Insurance leader generates coveted 360-degree view of customers in 90 days – “The Wall” Problem Why MongoDB Results • No single view of customer • 145 yrs of policy data, 70+ systems, 15+ apps • 2 years, $25M in failing to aggregate in RDBMS • Poor customer experience • Agility – prototype in 9 days; • Dynamic schema & rich querying – combine disparate data into one data store • Hot tech to attract top talent • Production in 90 days with 70 feeders • Unified customer view available to all channels • Increased call center productivity • Better customer experience, reduced churn, more upsell opps • Dozens more projects on same data platform
Single View of Customer Adding Flexibility and Scalability to Bouygues Telecom Problem Why MongoDB Results • No single view of customer • Perfomance and complexity • 2 years delay • Poor customer experience • Agility • Scalability • Dynamic schema & rich querying – combine disparate data into one data store • Easy data integration • Developed in 6 months • Unified customer view available to all channels • Increased call center productivity • New projects • Devops
Product Catalog Serves variety of content and user services on multiple platforms to 7M web and mobile users Problem Why MongoDB Results • MySQL reached scale ceiling – could not cope with performance and scalability demands • Metadata management too challenging with relational model • Hard to integrate external data sources • Unrivaled performance • Simple scalability and high availability • Intuitive mapping • Eliminated 6B+ rows of attributes – instead creates single document per user / piece of content • Supports 115,000+ queries per second • Saved £2M+ over 3 yrs. • “Lead time for new implementations is cut massively” • MongoDB is default choice for all new projects