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Internet of Things
Valerio BianchiMilan, January 14th, 2016
The Beginning
• 1977 – Larry Ellison, Bob Miner & Ed Oates create Software Development Laboratories
• 1978 – Oracle born
• 1979 – SDL rename themselves Relational Systems Inc. (RSI) and move to California. First commercial relational database released
First commercial relational database released
1981
La IBM produce i primi floppy disk nel 1970
Today
DIGITAL
ECONOMY
DEVELOPMENT
• Iterative
• Short development cycles
• New workloads
VOLUME OF DATA
• Petabytes of data
• Trillions of records
• Millions of queries per second
DATA TYPES
• Unstructured data
• Semi-structured data
• Polymorphic data
NEW ARCHITECTURES
• Horizontal scaling
• Commodity servers
• Cloud computing
90%of the data has
been created in the
last two years
80%of enterprise data
are unstructured
2xUnstructured data
is growing at a
double rate
Millions
of users on
global scale
New Pay-
for-value
models
Agile
vs.
Waterfall
Relational DBMS
Mental
Model
Relational Model
Scale up Costs up Performance
Down
Scalability and
Performance
Document
Model
RDBMS MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}
The Power of the Document Model
01
10JSON
Document Model
Designed to adapt to changes
Scalability, Performance and Cost
…Scale-out
…Linear cost
Linear
PerformanceCommodity
or in Cloud
Nexus ArchitectureR
ela
tio
na
l No
SQ
L
Expressive Query
Language
Strong
Consistency
Secondary Indexes
Flexibility
Scalability
Performance
Nexus ArchitectureR
ela
tio
na
lN
oS
QL
Expressive Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance
Some Examples
The massive volume and
increasingly unstructured nature
of IoT data has put new
demands on Bosch SI's entire
technology stack, especially the
underlying database
Rigid RDBMS data models lack
the flexibility, scale and real-time
analytics needed to quickly
capture, share, process and
analyze IoT data.
PROBLEM
The Bosch IoT Suite and the
integrated database from
MongoDB creates services that
gather data and deliver
immediate insight.
The Bosch IoT Suite collects
data from individual sensors and
equipment. MongoDB stores,
manages and analyzes all of this
event data in real-time.
MongoDB also stores business
rules that trigger alarms and
notifications.
SOLUTION
Allows limitless use cases: to
drive innovative apps in every
industry.
It can improve the retail
shopping experience with in-
store maps and personalized
notifications.
Create safer working conditions
in manufacturing environments.
Trace agriculture thru the food
chain to support farm-to-table
initiatives.
RESULTS
Bringing the power of big data to a new
range of Industrial Internet applications
Need to create innovative apps
that support corporate mission to
protect customers, improve
brand perception, and reduce
churn
Poor view of customers’
behavior at home, which can be
used to provide more compelling
pricing and better products
Unable to offer a new
experience around domestic
connected objects
PROBLEM
Build a scalable mobile app
allowing customers to integrate
domestic connected objects to
detect and prevent risk
Leverages flexible data model to
support specific APIs with third
parties: Philips Hue light bulbs,
NEST smoke detection, MyFox
cameras, and more in fast
evolving market
SOLUTION
Prototype built in 2 months;
deployed in production in 4
months
Able to prevent domestic risks
and assist customers in case of
incidents. Proactive alerting to
customers minimizes their risk,
creates customer loyalty
Great user experience improves
perception of AXA brand
RESULTS
Risk Mgt. for the Connected HomeDelivering on customer protection mission with MongoDB
{ name : "Valerio Bianchi",title : "Enterprise Account Executive, Italy",phone : "+39-334-6403398",location : "Milan, Italy",twitter : "@MongoDB",facebook : "MongoDB” }