Join this webinar as Ryan Betts, CTO of VoltDB, describes several data-as-a-service reference architectures for IoT and discuss a real use case highlighting how an in-memory operational database simplified a large-scale enterprise architecture to handle real-time data for IoT -- faster and smarter. View the webinar in its entirety here: http://learn.voltdb.com/WRIoT.html

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UNDERSTANDING THE OPERATIONAL
DATABASE INFRASTRUCTURE FOR IOT AND
FAST DATA

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AGENDA
• Framing IoT
• Locating the Data Opportunity
• The Role of the Operational DB

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FEEDBACK LOOPS OF INNOVATION & CONVERGENCE
Source: http://www.economist.com/node/21531109

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IOT CONNECTS TECHNOLOGIES

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IOT CONNECTS INDUSTRIES
Mobile Cloud Big Data Security Telco
Health Automotive Smart City Transport Energy

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VERTICALLY SUSTAINABLE

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IOT IS A DEEP STACK: TODAY’S FOCUS IS DATA
Device
Security & Policy
Communication
Edge Compute
More Networks
Centralized Compute
Data Services
Cloud Applications
Fast (in motion)
Streaming Analytics:
real time summary
aggregation, modeling
Transaction
Processing:
per-event decisions
using context + history.
Big (at rest)
Exploration:
data science,
investigation of large
data sets
Reporting:
recommendation
matrixes, search
indexes, trend and BI

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MACHINE LEARNING. OPERATIONS. ANALYTICS
The data management required for
centralized compute is the same stack
evolved for big data applica9ons.

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DATA MANAGEMENT: COMPONENTS
Embrace “one size
fits none”.
Balance tension
between DaaS and
Microservice
applica9on
isola9on.

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ROLE OF AN OPERATIONAL DATABASE
…at the 9me RDBMSs were
architected was the dumb
terminal, and vendors imagined
operators inpuGng queries
through an interac9ve terminal
prompt. Now it is a powerful
personal computer connected to
the World Wide Web.

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AWS IOT REFERENCE ARCHITECTURE

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Fast inbound events
requests
Application with
request/response
pattern for context
Event initiated,
automated action
Forwarding of
accumulated data to
OLAP or
Applications
Events
VoltDB
C*
Triggered
Alerting
Hadoop
1
3
2
1
2
3
4
EoD
Billing
4
Rule
Engine
FAST DATA: INGEST, ANALYTICS, TRANSACTIONS

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Ingest sensor readings from
millions of smart meters
Energy Validation process.
Determine id billing threshold
has been exceeded.
Initiate message to user of
dynamic rate change.
Categorize and filter by meter
type and rate table prior to
export to billing application
Events
VoltDB Triggered
Alerting
Hadoop
1
3
2
1
2
3
4
EoD
Billing
4
Rule
Engine
CUSTOMER EXAMPLE - SMART METER SYSTEM

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Ingest device
readings
Rule engine with
request/response
pattern for context
Alert/Alarm on
thresholds
Forwarding of
accumulated data to
long term storage
Events
VoltDB
C*
Triggered
Alerting
Hadoop
1
3
2
1
2
3
4
PgSQL
MDR
4
Rule
Engine
CUSTOMER EXAMPLE – OEM IOT PLATFORM

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Ingest exchange tick
data
Request/response
analyst queries
Publish change
events to ESB
Forward intra-day
data to downstream
applications
Events
VoltDB
App1
Triggered
Alerting
App3
1
3
2
1
2
3
4
App2
4
Intraday
Query
PATTERN EMERGES: FIN. SERVICES CUSTOMER

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REAL-TIME EVENT DECISIONING
PLATFORM
Deliver the best interac9on aligned
to each
individual customer in
real-­‐9me to drive customer
engagement & maximise business
results

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THE DATA, CLOUD & IoT CONNECTION
• IoT is a data driven application
• Data will drive cloud utilization
• IaaS low margin
• Apps drive margin
• Making the data useful drives value
• It’s not just storage, its operational
• The more data processed in the front end,
the more that will be stored in the cloud
CloudData
IoT

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Steam (40%)Electric (38%) Internal Combustion (22%)
1900: hundreds of makers. No consensus on “what does a car look like.”
1926: 50 manufacturers gone in previous 3 years. Model-T is 50% of entire market.
1900-1926: INNOVATION AND CONVERGENCE

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THANK YOU