By Aveek Bushan, Soluton Architecture, APAC Leader, MongoDB

1. Welcome
Key-Note
Aveek Bushan
aveekshith.bushan@mongodb.com
Solutions Architect – APAC Lead
Bengaluru Executive Seminar

2. 2
On Today…
Time
Topic
Presenter
14:00
Welcome
Keynote,
Session
on
“MongoDB
at
Scale”
Aveek
Bushan
Solu3on
Architecture,
APAC
Leader,
MongoDB
14:45
Business
Transforma=on
Case
Study
Prashanth
Victor
Senior
Director,
Product
Mgmt,
Tecnotree
15:15
High
Tea
16:00
Introduc=on
to
the
MongoDB
Partner
Ecosystem
Rajiv
Thapar
APAC
Director,
Channels
and
Partners,
MongoDB
16:05
Partner
Case
Study
Sa3sh
PV
Senior
Consultant,
Happiest
Minds
16:20
Why
and
How
Smart
Organiza=ons
are
moving
from
Rela=onal
to
MongoDB
Vigyan
Jain
Solu3ons
Architect,
MongoDB
17:00
MongoDB:
Your
Database
of
Choice
for
Real
Time
Analy=cs
Sandeep
L
Khuperkar
Director,
Ashnik
Technology
Solu3ons
Pvt
Ltd
17:15
Q&A
Session
17:30
Drinks
and
Networking

3. 3
Focus in the Region
MongoDB
Employees
-­‐
Last
Event
in
2014
in
Bangalore
• Sales
Team
• Consul3ng
Engineers
Rapid
Growth
Ever
Since,
with
• Solu3on
Architecture
Team
• Channels
and
Partners
Team
• Support
Engineers
MongoDB
Community
-­‐
• Strong
Customer
Eco-­‐system
Across
the
Country
• Vibrant
Partner
Eco-­‐system
• Rapid
Adop3on
• Events
and
Meet-­‐ups
across
the
Country

4. 4
Reach out to Us.. We are here!
Vijay
–
India
Sales
vijay.singh@mongodb.com
Rajiv
–
APAC
Channels
Rajiv.thapar@mongodb.com
Vigyan
–
Solu3on
Architecture
Vigyan.jain@mongodb.com
Mandeep
–
APAC
Sales
Mandeep.singh@mongodb.com
Kim
–
Opera3ons
Manager
Kim.kharkongor@mongodb.com
Guru
–
Consul3ng
Gururaj.bayari@mongodb.com

5. MongoDB at
Scale!
Aveek Bushan
aveekshith.bushan@mongodb.com
Solutions Architect – APAC Lead
Bengaluru Executive Seminar

6. 6
Born:
1949
When
he
started:
Tests
Career
Earnings:
?
Born:
1973
When
he
started:
Tests,
One
Dayers
Career
Earnings:
??
Born:
1992
When
he
started:
Tests,
One
Dayers,
T20s
Career
Earnings:
???
Over the Years…At Scale!

7. 7
Scale - Closer to Home
1956
IBM
350
Hard
Disk
5MB
of
storage
System
Cost:
160K$
1980
IBM
3380
1GB
of
storage
Cost:
50K$
2015
Mul=ple
Op=ons
1TB
of
storage
Cost:
0.8K$

8. 8
Over the Years – Scale!

9. 9
Scale Changes Everything!
Source:
The
Black
Swan
by
Nassim
Nocholas
Taleb

10. 10
The Black Swan Effect

11. 11
“Known” and “Unknown” Unknowns!
Known
Unknowns
• Can
be
Planned
For
• Through
BCP,
Risk
Matrix
etc
Unknown
Unknowns
• Difficult
to
Model
and
Foresee
• Impact
can
be
reduced
by
Diversifica3on
Across
Investments,
Business,
Markets
and
Product
Types

12. 12
What Does it Mean – IT Perspective
Posi3ve
Black
Swans
• Explosion
in
Data
• Exposure
to
Different
Types
of
Data
• Agility
in
IT
Infrastructure
• Ex:
Successful
New
Product
or
Market
Launch
Nega3ve
Black
Swans
• Globally
Distributed
IT
Infrastructure
• No
Vendor
Lock-­‐In
• Easy
Deployment
Models
• Ex:
Natural
or
Man-­‐made
Disasters,
Market
Changes
Gaussian
World
• Structured
Data
• Predictable
Growth
in
Data
Volume
• Lower
Cost
of
Overall
Opera3on
• Ex:
Tradi3onal
Applica3ons

13. 13
Positive Black Swans - Data
Posi3ve
Black
Swans
• Explosion
in
Data
• Exposure
to
Different
Types
of
Data
• Agility
in
IT
Infrastructure
• Ex:
Successful
New
Product
or
Market
Launch
Horizontal
Scalability
Dynamic
Data
Model
Performance
Agility
Geospa3al
Informa3on

14. 14
Negative Black Swans - Data
Nega3ve
Black
Swans
• Globally
Distributed
IT
Infrastructure
• No
Vendor
Lock-­‐In
• Easy
Deployment
Models
• Ex:
Natural
or
Man-­‐made
Disasters,
Market
Changes
Geographically
Distributed
Clusters
Built
on
Commodity
Hardware
Cloud-­‐Ready
Flexible
Data
Model
Low
Cost
Solu3on

15. 15
Gaussian World - Data
Gaussian
World
• Structured
Data
• Predictable
Growth
in
Data
Volume
• Lower
Cost
of
Overall
Opera3on
• Ex:
Tradi3onal
Applica3ons
Strong
Consistency
Strong
Query
Model
Structured
Data
*
Manageability
Partner
Support

16. Combining the best of both Worlds!

17. 17
The World Has Changed
Data
• Volume
• Velocity
• Variety
Time
• Iterative
• Agile
• Short Cycles
Risk
• Always On
• Scale
• Global
Cost
• Open-Source
• Cloud
• Commodity

18. 18
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance
Relational

19. 19
NoSQL
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance

20. 20
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance
Relational NoSQLNexus Architecture

21. 21
Nexus Architecture – R3.2
• WiredTiger
the
default
Storage
Engine
• Encrypted
Storage
Engine
• In-­‐Memory
Storage
Engine
Broader
use
case
poraolio
• Document
Valida3on
• Mul3-­‐Data
Center
Deployments
• Faster
Fail-­‐overs
Mission-­‐
cri=cal
apps
• BI
Connector
• $lookup
• Aggrega3on
Enhancements
• MongoDB
Compass
New
tools
for
new
users
DISCLAIMER:MongoDB'sproductplansareforinformationalpurposesonly.MongoDB'splansmay
changeandyoushouldnotrelyonthemfordeliveryofaspecificfeatureataspecifictime.

22. 22
Farming At Scale!
Use
Case
• Built
“Farmsight”,
an
IoT
Applica3on
that
stores
and
aggregates
data
from
equipment
sensors,
then
presents
it
as
an
analy3cs
dashboard
MongoDB
Differen3ator
• Handle
Large
Volumes
of
Data
• Handle
Data
Variety
Value
to
the
Customer
• First
to
market
with
unique,
intelligent
solu3on
that
helps
farmers
op3mize
machine
and
farm
opera3ons.
Rolled
out
in
just
6
months
Leverage Data & Tech. to Maximize Competitive Advantage

23. 23
How Can We Help!
MongoDB Enterprise Advanced
The best way to run MongoDB in your data center
MongoDB Cloud Manager
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.

24. 24
For More Information
Resource Location
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
Documentation docs.mongodb.org
MongoDB Downloads mongodb.com/download
Additional Info info@mongodb.com

25. 25
Black Swans are a Reality!
“The
strategy
for
the
discoverers
and
entrepreneurs
is
to
recognize
opportuni=es
when
they
present
themselves…
the
reason
free
markets
work
is
because
they
allow
people
to
be
lucky…The
strategy
is,
then,
to
3nker
as
much
as
possible
and
try
to
collect
as
many
Black
Swan
opportuni=es
as
you
can..”
-­‐
Nassim
Nicholas
Taleb,
The
Black
Swan

26. Thank You!
Aveek Bushan
Email: aveekshith.bushan@mongodb.com
Twitter: @aveekshith