1. Mongo DB
OPEN SOURCE, HIGH PERFORMANCE DATABASE
SEMINAR GUIDE: PRESENTED BY:
MR.M.V.VAIDYA NIKHIL SATISH PADMAWAR
(2012BIT028)

2. Outlines
 Mongo DB
 Introduction to 10gen
 Hawk eye @MongoDB
 Features
 Document Store
 Comparison
 Collections
 Replication
 Sharding
 CRUD
 NoSQL Type
 CAP Theorem
 Installation Process

3. 10gen is the company behind MongoDB.
Founded in 2007
 Dwight Merriman, Eliot Horowitz
 Doubleclick, Oracle, Marklogic, HP
Worldwide Expanding Team
 140+ employees
 NY, Palo Alto, London, Dublin, Sydney
MongoDB’s Office,Palo Alto,California
Set the direction &
Contribute code to
MongoDB
Foster
Community
&
ecosystem
Provide
commercial
services
Provide MongoDB
management Services

4. Why MongoDB
 Schema-less
Pain of ‘Alter table’(Wide Application in E-commerce)
 No-Joins
Complexity of Join
 Data Type
Polymorphic data type
ex. A=1 and A=Nanded
 Big Size Limit per Document(16 MB per Doc)

5. What is MongoDB?
 Data model: Using BSON (binary JSON), developers can easily map to modern object-oriented
languages without a complicated ORM layer.
 ORM
 BSON
Lightweight, Traversable, Efficient.

6. MongoDB is the leading NoSql Solution
On In deed's Fastest Growing Jobs
Google Searches
Jasper soft Big data Index
MongoDB Increasing Its Dominance
Demand
For MongoDB,
the document-
oriented NoSQL
database, saw
the biggest
spike with over
200% growth in
2011.

7. Features
 Document-Oriented Storage
 Full Index Support
 Querying
 Replication and High Availability
 Auto Sharding
Fast In-place Updates
 Map/Reduce
 Operating System : Cross-Platform

8. Agile and Scalable
It is easy to
Code,
Scale, and
Manage
Database.

9. MongoDB is
Easy to
Use
General
Purpose
Fast &
Scalable
Rich DATA
Model
Full Featured
Indexes
Sophisticated
Query Language
Easy Mapping
To Object
Oriented Code
Operates at In
Memory Speed
Wherever
Possible
Native
Language
Drivers in
Auto-Sharding
Built in
Simple to Setup
and Manage
Dynamically
Add/remove
Capacity With
No Downtime

10. Document Store
RDBMS MongoDB
Database Database
Table, view Collection
Row Documents(JSON,BSON)
Column Field
Index Index
Join Embedded Document
Foreign Key Reference
Partition Key Shard Key

11. Relational Database MongoDB

12. Collections
 Collections of MongoDB is like table in SQL
 Dynamic schema
 No '$' or '0' in name of collection
 Capped collections

13. Replication
 Redundancy and Failover
 Zero downtime for upgrades and maintaince
 Master-Slave replication
Strong Consistency
Delayed Consistency
 Geospatial Features
Copying

14. Sharding
 Partition your data
 Scale write throughput
 Increase capacity
 Auto-balancing
One big database
Splitting of data

15. CRUD
 Create
db.collection.insert( <document> )
db.collection.insert({'author':'Bob','title':'Introduction to mysql','article':'mongodb is open source database'})
 Read
db.collection.find( <query>, <projection> )
db.collection.find({'author':''Bob}
 Update
db.collection.update( <query>, <update>, <options> )
db.collection.update({'author':'Bob'},{'$set':{'title':'Introduction to mongoDB'}})
 Delete
db.collection.remove( <query>, <justOne> )
db.collection.remove({'author':'Bob'})

16. CRUD Example
> db.user.insert({
first: "John",
last : "Doe",
age: 39
})
> db.user.update(
{"_id" : ObjectId("51…")},
{
$set: {
age: 40,
salary: 7000}
}
)
> db.user.find ()
{
"_id" : ObjectId("51…"),
"first" : "John",
"last" : "Doe",
"age" : 39
}
> db.user.remove({
"first": /^J/
})

17. MongoDB is Easy to Use
{
title: ‘MongoDB’,
contributors: [
{ name: ‘Eliot Horowitz’,
email: ‘eliot@10gen.com’ },
{ name: ‘Dwight Merriman’,
email: ‘dwight@10gen.com’ }
],
model: {
relational: false,
awesome: true
}
}

18. START TRANSACTION;
INSERT INTO contacts VALUES
(NULL, ‘joeblow’);
INSERT INTO contact_emails VALUES
( NULL, ”joe@blow.com”,
LAST_INSERT_ID() ),
( NULL, “joseph@blow.com”,
LAST_INSERT_ID() );
COMMIT;
db.contacts.save( {
userName: “joeblow”,
emailAddresses: [
“joe@blow.com”,
“joseph@blow.com” ] } );
MySQL MongoDB

19. NOSQL(Not Only SQL)Type
1) Key-Value databases
{
"Name": "John",
"Age": 20,
"address": "Nanded"
}
2) Document databases
{
"name": "John",
"age": 25,
"address": {
"streetAddress": "21 2nd
Street",
"city": "Nanded",
"state": "Maharashtra",
"postalCode": "403414”
},
"children": [“Anshu”,”chetan”],
}

20. Continue…
3) Wide Column Store / Column Families
Row Columner
Id Name Address Age
1 Nicks Nanded 21
2 Alice Mumbai 25
3 Bob Delhi 18
4 Jhon Pune 27
Id Name
1 Nicks
2 Alice
3 Bob
4 Jhon
4) Graph Databases

21. CAP Theorem
 Three properties of a system
Consistency
Availability
Partitions

22. JSON
Key value
{
“bookName”:”The Da Vinci Code”,
“authorName”:”Dan Brown”,
“pages”:320,
“ISBN”:”53453444-234”
}

23. Documents
{
“_id”: ObjectId("52452ea71c5619b639000005")
“bookName”:”The Da Vinci Code”,
“authorName”:”Dan Brown”,
“pages”:320,
“publishedOn”: ISODate("2013-09-27T07:07:19.610Z")
“tag”:[”novel”,”mystery”,”drama”,”action”]
}
Unique identifier
Date
Array list

24. Database
 Admin
 Local
 Config (Supports Sharded Cluster Operation)

25. Installation
 echo 'deb http://downloads-distro.mongodb.org/repo/ubuntu-upstart dist 10gen' | sudo tee
/etc/apt/sources.list.d/mongodb.list
 sudo apt-get update
 sudo apt-get install -y mongodb-org

26. mongo
one of the considerable advantage of using
MongoDB is-
we can calculate distances by providing latitude
and altitude in MongoDB query.
mysql

27. Few Commands
Connect
mongo
show dbs
use <db name>
show collections
use <collection name>

28. A MongoDB Users
MongoDB is widely used by many enterprises. To name a few:
 Disney
 MTV
 EA Sports
 Craigslist

29. References
 E. F. Codd. 1970. A relational model of data for large shared data
banks. Commun. ACM 13, 6 (June 1970), 377-387.
DOI=10.1145/362384.362685
http://doi.acm.org/10.1145/362384.362685
 ISO/IEC 9075-1:2008: Information technology – Database languages –
SQL – Part 1: Framework (SQL/Framework)

30. Conclusion
MongoDB, with its flexible schema, distributed deployment, aggregation and low latency
is typically suited for the following kind of applications:
 Content Management
 Inventory Management
 Game Development
 Social Media Storage
 Database for sensor streams

31. Thank You For Your Attention!