MongoDB is an open-source, document-oriented, NoSQL database that provides scalability, performance, and high availability. It is written in C++ and stores data in flexible, JSON-like documents, allowing for easy querying and retrieval of data. MongoDB is commonly used for applications that require scalability and large datasets, and provides features like auto-sharding, replication, and rich queries.

1. By
C . Enoch Joshua

2. What is MONGO DB?
No Sql
Database
Open Source Cross Platform
Document
Oriented
Written in c++

3.  All the modern applications require big data,
 Fast features development,
 Flexible deployment,
 Older database systems not enough competent,
 Auto - sharding
 Rich queries
 Document Oriented Storage − Data is stored in the form of JSON style
documents.

4. Where to Use Mongo DB?

5. Main purpose to build Mongo DB
 Scalability
 Performance
 High Availability
 Scaling from single server deployments to large, complex multi-site
architectures.
 Develop Faster
 Deploy Easier

6. History of Mongo DB
 The initial development of Mongo DB began in 2007 when the company was
building a platform as a service similar to window azure.
 Mongo DB was developed by a New York based organization named 10gen
 Later in 2009, it is introduced in the market as an open source database server
 The first ready production of Mongo DB has been considered from version
1.4 which was released in March 2010.
 MongoDB2.4.9 was the latest and stable version which was released on
December 22, 2016.

7. Who uses Mongo DB
7

8. Installing Mongo DB on Windows
1.Download the Mongo DB binary archive:

9. 2.Extract Mongo DB archive:
 Go ahead and extract archive. After extracting, you will get the directories
inside archive as follows
 here , bin directory contains the binaries in form of executables , such as
mongod.exe, mongo.exe, monogexport.exe etc.

10. 3.Setup up configuration to start stop Mongo DB:
 For starting and stopping the Mongo DB server, we need only
the bin/mongod.exe, which is the daemon process executable for Mongo DB.
Using command line options:
 With use of these command line options, we configure mongo daemon process

11.  Use the following commands to start the server process.
 Change to bin directory.
 now type following command to start the mongod process.
 While starting, Windows firewall may block the process
 Click “Allow access“ to proceed. After successful execution of command ,
it will show logging info in standard console itself
1 cd I:Serversmongodbbin
1 mongod --dbpath I:Serversdata --port 27017

13. D/B RDBMS & Mongo DB
RDBMS MongoDB
Database Database
Table Collection
Tuple/Row Document
column Field
Table Join Embedded Documents
Primary Key Primary Key (Default key _id provided
by mongo db itself)

14.  Example:
 Suppose a client needs a database design for his blog/website and see the
differences between RDBMS and Mongo DB schema design.
 In RDBMS schema will have minimum three tables.

15.  While in Mongo DB schema,
design will have one
collection post and the
following structure.
 So while showing the data, in
RDBMS you need to join
three tables and in Mongo
DB, data will be shown from
one collection only.
{ _id: POST_ID
title: TITLE_OF_POST,
description: POST_DESCRIPTION,
by: POST_BY,
url: URL_OF_POST,
tags: [TAG1, TAG2, TAG3],
likes: TOTAL_LIKES,
comments: [
{
user:'COMMENT_BY',
message: TEXT,
dateCreated: DATE_TIME, l
ike: LIKES
},
{
user:'COMMENT_BY',
message: TEXT,
dateCreated: DATE_TIME,
like: LIKES
}
] }

16. Mongo DB – Data Types

17. Mongo DB - Create Database
The use Command:
 Mongo DB use DATABASE_NAME is used to create database. The command
will create a new database if it doesn't exist, otherwise it will return the existing
database.
Syntax:
Example:
 If you want to create a database with name <mydb> then,
use DATABASE_NAME
>use mydb
switched to db mydb
>db
mydb

18. Mongo DB - Drop Database
 MongoDB db.dropDatabase() command is used to drop a existing database.
Syntax:
Example:
First, check the list of available databases by using the command, show dbs.
db.dropDatabase()
>show dbs
local 0.78125GB
mydb 0.23012GB
test 0.23012GB
>

19. If you want to delete new database <mydb>,then dropDatabase() command would
be as follows
Now check list of databases.
>use mydb
switched to db mydb
>db.dropDatabase()
>{ "dropped" : "mydb", "ok" : 1 }
>
>show dbs
local 0.78125GB
test 0.23012GB
>

20. Mongo DB - Create Collection
 Syntax:
 Examples:
db.createCollection(name, options)
>use test
switched to db test
>db.createCollection("mycollection")
{ "ok" : 1 }
>
>db.createCollection("mycol", { capped : true, autoIndexID : true, size :
6142800, max : 10000 } )
{ "ok" : 1 }
>

21. Mongo DB - Drop Collection
 Syntax:
 Example:
db.COLLECTION_NAME.drop()
>use mydb
switched to db mydb
>show collections
Mycol
mydb
>db.mycollection.drop()
true
>show collections
mycol

22. Replication

23. Multi Replication
 Data can be replicated to multiple places simultaneously
 Odd number of machines are always needed in a replica set

24. Single Replication
 If you want to have only one or odd number of secondary, you need to
setup an arbiter
 Arbiter will always be the arbiter and can only vote. But primary can be
primary also can step down as secondary.

25. Failover
 When primary fails, remaining machines vote for electing new
primary

26. Sharding
 A method for storing data across multiple machines
 Data is partitioned using Shard Keys

27. Sharded Cluster
 shard: Each shard contains a
subset of the sharded data.
Each shard can be deployed as
a replica set.
 mongos: The mongos acts as a
query router, providing an
interface between client
applications and the sharded
cluster.
 config servers: Config servers
store metadata and
configuration settings for the
cluster.

28. Data Partitioning: Range Based
 A range of Shard Keys stay in a chunk
28

29. Data Partitioning: Hash Based
 A hash function on Shard Keys decides the chunk
29

30. Optimizing Shards: Splitting
 In a shard, when size of a chunk increases, the chunk is divided into two
30

31. Optimizing Shards: Balancing
 When number of chunks in a shard increase, a few chunks are migrated to
other shard
31

32. Map-Reduce
 Map-reduce is a data processing paradigm for condensing large volumes of data
into useful aggregated results. For map-reduce operations, Mongo DB provides
the map Reduce database command.
 Mongo DB applies the map phase to each input document.
 The map function emits key-value pairs.
 For those keys that have multiple values, Mongo DB applies the reduce phase,
which collects and condenses the aggregated data.
 Mongo DB then stores the results in a collection.