MongoDBThe Database for Modern Applications
Solutions Architect, MongoDB
Henrik Ingo
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The 70s...
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1979: Sony Walkman
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1974: Post-it notes
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1971: First Man on the Moon
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1966: Telefax (popularized during the 70s)
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1977: Apple II, the first PC
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The Relational Database
Things the RDBMS is optimized for...
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Disk space
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Data integrity
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Waterfall Development Cycle
Business
RequirementssAnalysis
Technical
Requirements
DataBase
Schema
Design
Software
DevelopmentQA
Production
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Flexibility (seriously)
/* ---------------------------------- *//* ----- Begin the PL/SQL block ----- *//* ---------------------------------- */EXEC SQL EXECUTE
DECLAREinsufficient_funds EXCEPTION;old_bal NUMBER;min_bal CONSTANT NUMBER := 500;
BEGINSELECT 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_balWHERE account_id = :acct;
INSERT INTO journalVALUES (:acct, 'Debit', :debit, SYSDATE);
:status := 'Transaction completed.';ELSE
RAISE insufficient_funds;END IF;....
The reality in 2014...
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Business logic in PL/SQL is not a best practice
?
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RDBMS is a poor match to OO
Relational
Database
Object Relational
MappingApplication
Code XML Config DB Schema
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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
PrototypingReview
Production
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Data exists in diverse sources......beyond our control, btw.
social media
sensors
Legacy
RDBMSLegacy
RDBMSLegacy
RDBMS
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
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
RDBMSsystems
RDBMS
Staging,Data preparation
DWH
Graphing SW
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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
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Branch out
MongoDB
RDBMS
app
OriginalDB
New functionalityor Big Data
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