Presented by, Emil Berthelsen, Principal Analyst at Machina Research. Emil discusses the market landscape for M2M and IoT, and the impact of these market developments on database requirements.

1. Machina Research
How M2M and IoT are changing
the playing field of data
M2M/IoT market landscapes and the ‘new’ in databases
September 2014

2. About us
 The leading research/consulting firm focusing on the emerging
opportunity for new connected devices and applications, i.e.
M2M, IoT and Big Data
• Support our clients through
• Machina Research Advisory Service – our multi-client
annual subscription service comprising forecasts, reports and
access to the analysts (see below)
• Custom Research & Consulting –client-specific research
• We have the most focused research on M2M and IoT fields of
any analyst firm in the world: we provide the most granular
forecasts for the global M2M and IoT opportunities, supported
by the most robust analysis of market issues and dynamics
• Machina Research was founded in 2010, and brings to its clients
a professional team of industry analysts with many years of
experience in M2M research and consulting
Machina Research 2

3. What is M2M and IoT, and why should we
take note of it?
M2M and IoT
• is not just about the €1.5
trillion revenue opportunity
by 2023
• or that more than 34.1 billion
connections will have been
implemented by end of 2023
• it is about creating new
services which
• improves people’s lives
• delivers better customer
experiences
• generates improved
efficiency
• reduces costs and waste
40
1,800
35
1,600
30
1,400
25
1,200
20
1,000
15
800
10
600
5
400
0
billions
Figure 1: Global M2M & IoT revenue
opportunity (in euro billions)
[Source: Machina Research, 2014]
2: connections
New Services
[Source: Machina Research, 2014]
M2M PCs, tablets, handset data
200
0
Euro billions
Machina Research 3

4. An accelerated pace is observed in data
creation and storage
Internet of Things
• Data is now being generated at an
accelerated pace – from astronomical
surveys, to financial transactions, to retail
data, and to hospital imaging or CCTV
data – the “digital” library of Alexandria
• An ever increasing amount of data from
social media like Facebook, Twitter,
SnapChat and more ‘traditional’
communications’ channels like SMS and
voice calls
• Historically, costs for storing this data has
led to significant “information disposal,”
but falling storage prices as well as
potential data value and the ability to
data mine unstructured data has led to
new business models
• M2M and IoT data – through the growing
number of connections – continues to
add to the acceleration of Big Data
Machine-to-Machine
Business-to-Business
Transactions
People-to-People
Interactions
Within the
enterprise
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5. Connections are becoming increasingly
more pervasive in the Internet of Things
Growth in connections generates an
unparalleled scale of data
Smart Homes
Connected Cars
Intelligent Buildings
Intelligent Transportation
Smart Meters and Grids
Sensors
Devices
Systems
Things
Processes
People
Industries
Products
Services
Internet of Things
Machine-to-Machine
Isolated
telemetry
and
telematics
Monitored
(autonomous, disconnected)
Building
automation
Manufacturing
Security
Utilities
Remotely
controlled and
managed
Systems
Smart Retailing
Smart Enterprise
Management
Smart Systems
(Intelligence in the
Subnets of Things )
Internet of
Things
Tens Hundreds Thousands Millions Billions Connections
Machina Research 5

6. Some examples of M2M and IoT
WATER LEVEL
MONITOR
Security & Access controls
AV sources
Home network
infrastructure
Building
automation
CONNECTED CAR
Entertainment & Infotainment
Security &
Tracking
eCall
Solar panels
White goods
SMART HOME &
CONSUMER ELECTRONICS
Navigation
Manufacturer data
Electric vehicles
Smart grids
Renewable
energy sources
Smart meters
Insurance
SMART
UTILITIES
SUBNET OF THINGS:
VIRTUAL POWER PLANTS
Machina Research 6

7. M2M and IoT solutions are complex and
made up of several components
Devices
Networks
Platforms
Internet of
Things
Connected things,
products, systems,
applications, etc.
Security
Storage
Data Processing Applications
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8. Doing more of the same will no longer
meet the requirements
A new mindset and technology is
required for M2M & IoT
A changing approach to databases in
M2M and the Internet of Things
Machina Research 8

9. Evolution from M2M to IoT introduces
new data management requirements
Pre-IoT (M2M) Internet of Things Data
Big data
(scale & heterogeneity)
Large estates of
heterogeneous devices
Limited estate of
devices
Agile models
(agility & extensibility)
Evolving applications and
data sets
Single, fit-for-purpose
applications
Different data types
(flexibility)
All forms of data including
unstructured data
Structured / Semi-structured
data
Real-time data
analytics
(speed & performance)
Real-time and parallel
processing with
actionable insights
Alerts and alarms
Consistency
(integrity & consistency)
Open and shared data,
continuously evolving
Specific data sets
Machina Research 9

10. Five important characteristics emerge in
IoT when dealing with data management
Data
Big data
Agile models
Data types
Real-time data
analytics
Consistency
Scalability
Agility
Flexibility
Speed
Integrity
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11. New characteristics are addressed
at different levels by different
types of databases
Scalability
Agility
Flexibility
Speed
Integrity
Auto sharding /
partitioning
Schema structures
Data types
Performance, MPP,
fast query
ACID
NoSQL NewSQL
SQL
Machina Research Low High
11

12. Different databases with different strengths
– enterprises will need to understand what
applications need
NoSQL NewSQL SQL
Scalability, Agility &
Flexibility
Scalability & Speed Integrity & Speed
Machina Research 12

13. Understanding what your database
needs to handle is key
• What scale of data is involved? Thousands of records, millions of
records per hour?
– question of scalability of the database and performance
• How much of the data needs to be queried, and how often would
you expect to create new queries?
– ability and agility to create new queries and new data models
• What kind of data is generated from your connected devices? Now
and in the near future?
– difference between structured/semi-structured/unstructured
• What is the ‘criticality’ of the application in terms of processing
data quickly (fast)?
– low latency and performance (speed) of queries
• Are there strict compliance rules that need to be followed?
– Data integrity and consistency become paramount
Machina Research 13

14. For the majority of applications
in IoT, scalability, agility and
flexibility will be key
NoSQL NewSQL SQL
Scalability
Agility
Flexibility
Scale of the data
Dynamic nature of
applications
Structure of data
Machina Research Low High
14
Speed
Integrity
Performance, MPP,
fast query
ACID

15. Answering ‘how M2M and IoT are
changing the playing field of data’
• Significant scale and requirements change
in the market between M2M and IoT
• With the focal point shifting from device
and connectivity management in M2M to
applications and data in M2M and IoT, five
new characteristics emerge
• In M2M and IoT, scalability, agility and
flexibility will be priorities in applications,
and NoSQL and NewSQL databases will be
fairly well aligned with these requirements
Machina Research 15

16. Thank You !!!
Machina Research

17. Machina Research
Analyst Team
Matt Hatton, Director & Founder
matt.hatton@machinaresearch.com
Mobile: +44 7787 577886
Skype: mattyhatton
Twitter: @MattyHatton
Blog: wirelessnoodle.blogspot.com
Jim Morrish, Director & Founder
jim.morrish@machinaresearch.com
Mobile: +44 7747 632428
Skype: jim.morrish
Twitter: @jimmorrish
Blog: jim-morrish.blogspot.com
Emil Berthelsen
Principal Analyst (UK)
emil.berthelsen@machinaresearch.com
Mobile: +44 7714 671539
Skype: embe-machinaresearch
Twitter: Emil_Berthelsen
Emma Buckland
Principal Analyst (UK)
emma.buckland@machinaresearch.com
Mobile: +44 7950 887505
Skype: elab1972
Andy Castonguay
Principal Analyst (USA)
andy.castonguay@machinaresearch.com
Mobile: +1-619-888-1397
Skype: castonga
Alex Chau
Principal Analyst (Asia)
alex.chau@machinaresearch.com
Mobile: +852 9325-5501
Skype: alexkchau
Godfrey Chua
Principal Analyst (USA)
godfrey.chua@machinaresearch.com
Mobile: +1 617 388 4800
Skype: godychua
Jeremy Green
Principal Analyst (UK)
Jeremy.green@machinaresearch.com
Mobile:+44 790 358 1858
Skype:jeremy_green
Margaret Ranken
Associate Principal Analyst (UK)