The document discusses the advantages of using MongoDB over traditional relational databases (RDBMS) for modern applications, highlighting benefits such as flexibility, scalability, and improved developer productivity. It presents case studies where MongoDB effectively integrated diverse data sources, reduced project timelines, and enhanced customer experiences. The content illustrates the growing need for databases that can handle big data characteristics like volume, velocity, and variety.

1. MongoDB
The Database for Modern Applications
Solutions Architect, MongoDB
Henrik Ingo

2. 2
The 70s...

3. 3
1979: Sony Walkman

4. 4
1974: Post-it notes

5. 5
1971: First Man on the Moon

6. 6
1966: Telefax (popularized during the 70s)

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1977: Apple II, the first PC

8. 8
The Relational Database

9. Things the RDBMS is optimized for...

10. 10
Disk space

11. 11
Data integrity

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Waterfall Development Cycle
Business
Requirementss
Analysis
Technical
Requirements
DataBase
Schema
Design
Software
Development
QA
Production

13. 13
Flexibility (seriously)
/* ---------------------------------- */
/* ----- Begin the PL/SQL block ----- */
/* ---------------------------------- */
EXEC SQL EXECUTE
DECLARE
insufficient_funds EXCEPTION;
old_bal NUMBER;
min_bal CONSTANT NUMBER := 500;
BEGIN
SELECT bal INTO old_bal FROM accounts
WHERE account_id = :acct;
-- If the account doesn't exist, the NO_DATA_FOUND
-- exception will be automatically raised.
:new_bal := old_bal - :debit;
IF :new_bal >= min_bal THEN
UPDATE accounts SET bal = :new_bal
WHERE account_id = :acct;
INSERT INTO journal
VALUES (:acct, 'Debit', :debit, SYSDATE);
:status := 'Transaction completed.';
ELSE
RAISE insufficient_funds;
END IF;
....

14. The reality in 2014...

15. 15
Business logic in PL/SQL is not a best practice
?

16. 16
RDBMS is a poor match to OO
Relational
Database
Object Relational
Mapping
Application
Code XML Config DB Schema

17. 17
Document Data Model
Relational 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, … }
}
}

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Developers are more productive

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Iterative development
Business
Requirementss
Rapid
Prototyping
Review
Production

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Data exists in diverse sources...
...beyond our control, btw.
social media
sensors
Legacy
RDBMS
Legacy
RDBMS
Legacy
RDBMS

21. Big Data?

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Big Data is all about
Volume
Velocity
Variety

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You want a DB that has
Volume
Velocity
Variety
Scale-out
Low latency
Flexible schema

24. Typical MongoDB projects
for Oracle experts

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Data Hub
CRM CRM CRM
MongoDB
Dashboard

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Insurance leader generates coveted 360-degree view of
customers in 90 days – “The Wall”
Case
Problem Why MongoDB Results
• No single view of
customer
• 145 yrs of policy data,
70+ systems, 15+ apps
• 2 years, $25M trying to
aggregate in RDBMS –
failed
• Agility – prototype in 5
days; production in 90
days
• Dynamic schema & rich
querying – combine
disparate data into one
data store
• Hot tech to attract top
talent
• Increased call center
productivity
• Better customer
experience, reduced
churn, more upsell opps
• Dozens more projects in
the works to leverage
this data platform

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Staging hub
MongoDB
RDBMS
systems
RDBMS
Staging,
Data preparation
DWH
Graphing SW

28. 28
Archive
Archive
App
(MySQL)

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Stores billions of posts in myriad formats
with MongoDB
Case
Problem Why MongoDB Results
• 1.5M posts per day,
different structures
• Inflexible MySQL,
lengthy delays for
making changes
• Data piling up in
production database
• Poor performance
• Flexible document-
based model
• Horizontal scalability
built in
• Easy to use
• Interface in familiar
language
• Initial deployment held
over 5B documents and
10TB of data
• Automated failover
provides high
availability
• Schema changes are
quick and easy

30. 30
Branch out
MongoDB
RDBMS
app
Original
DB
New functionality
or Big Data