Build Application With MongoDB

View MongoDB Dev and Admin course details at www.edureka.co/mongodb

Build application with MongoDB

www.edureka.co/mongodbSlide 2

Objectives

At the end of this module, you will be able to

Understand the NoSQL Databases

CAP Theorem

MongoDB Introduction

MongoDB Architecture

CRUD Operations

Demo on integration of MongoDB with Java Application


Data Base Management System - History

In a last decades RDBMS have been successful in solving problems related to storing, Serving and processing data.

RDBMS are adopted for

Online transaction processing ( OLTP ) Online analytical processing ( OLAP )

RDBMS/OLTP/Real Time DSS/OLAP/DW

OracleMySQLMS SQLDB2

NetezzaSAP HanaOracle Express

But Challenges Ahead?


Challenge with ‘V’s

• Volume

• Velocity

• Variety

• Veracity

• Variability

• Volatility

• Value

RDBMS

NoSQL


Why NoSQL

Bigger Data Handling Capability :NoSQL distributed databases, allow data to be spread across thousands of commodity hardware.

Elastic scaling : Scale out the storage rather than scale up by adding commodity hardware.

No Schema or Fixed Data model :Data can be inserted in a NoSQL database without first defining a rigid database schema. So the format or data model being inserted can be changed any time, without application disruption.

Integrated Caching Facility:In order to increase data output and performance advance NoSQL techniques cache data in system memory.

Data complexity :data that is stored and managed in different locations or data centers.


Advantages of NoSQL

• Distributed Architecture: easy to scale-out, easy to manage large number of nodes

• First Reads: Satisfying ‘write once, read many times’ behaviour

• Easy Replication: The failover solution

• Higher Performance: An architecture providing much higher per-node performance than the traditional SQL-based databases

• Schema Free: Data model with dynamic and flexible schema

• Fast Development: No need of the additional ORM layer

To achieve the same, we compromise on:

No joinsNo ACID transaction


CAP theorem states that there are 3 basic requirements which exist in a special relation when designing applications for a distributed architecture.

Consistency

Availability

PartitionTolerance

CAP Theorem

This means that the system is always on (guaranteedservice availability), no downtime.

This means that the system continues to function even if thecommunication among the servers is unreliable, i.e. the serversmay be partitioned into multiple groups that cannot communicatewith one another.

This means that the data in the database remains consistent afterthe execution of an operation. For example, after an updateoperation all clients see the same data.

We must understand the CAP theorem when we talk about NoSQL databases or in fact when designing any distributed system.


CAP provides the basic requirements for a distributed system tofollow 2 of the 3 requirements.

Theoretically it is impossible to fulfill all 3 requirements.

Therefore, all the current NoSQL database follows the differentcombinations of the C, A, P from the CAP theorem.

CAP Theorem and NoSQL Databases

CA - Single site cluster, therefore all nodes are alwaysin contact. When a partition occurs, the system blocks.

CP - Some data may not be accessible, but the rest isstill consistent/accurate.

AP - System is still available under partitioning, butsome of the data returned may be inaccurate.


Basically Available indicates that the system does guarantee availability, in terms of the CAP theorem.

Basically Available

Soft State indicates that the state of the system may change over time, even without input. This is because of the eventual consistency model.

Soft State

Eventual Consistency indicates that the system will become consistent over time, given that the system doesn't receive input during that time.

Eventual Consistency

A BASE system gives up on consistency.

NoSQL Database - A BASE not ACID System


~ 150 No SQL Database are there in Market

~150

NoSQL Database – Not a Panacea


Key Value Store

Memcached

Coherence

Redis

Column

Cassandra

Hbase

Accumulo

Document Oriented

MongoDB

Couch DB

Cloudant

Graph Stores

Neo4J

Oracle NoSQL

HyperGraphDB

Types of NoSQL Databases


1000 TPS

Caching Layer

300 ~ 500 SQLTransaction

100 ~ 200 SQL Transaction

1000 TPS

WEB APPLICATION

RDBMS1

Applications Changing Data

RDBMS1

A Traditional Database Solution


WEB APPLICATION

5000 TPS

A NoSQL Database Solution

Applications Changing Data

Application grows with user base and data volume

5000 TPS


MongoDB is an Open-source database.

Developed by 10gen, for a wide variety of applications. Now it is named as MongoDB.

It is an agile database that allows schemas to change quickly as applications evolve.

Scalability, High Performance and Availability.

By leveraging in-memory computing. MongoDB’s native replicationand automated failover enableenterprise-grade reliability andoperational flexibility.

MongoDB Overview

Overview


Open Source Document Storage Object Oriented

Written in C++ Easy to Use Full Index Support

What is MongoDB?


Replication and High Availability Auto Sharding Easy Query

Map Reduce Gird FS Support from Expert

What is MongoDB? (Contd.)

MongoDB Replica set

Application


In RDBMS schema design for above requirements will have minimum 3 tables.

posts

id

title

description

url

likes

post_by

tags

id

post_id

tag

comments

Comment_id

post_id

by_user

message

date_time

likes

∞1 1

∞

Data Modeling Example in RDBMS and MongoDB


While in MongoDB schema design will have onecollection post and has the following structure.

So while showing the data, in RDBMS we need to jointhree tables and in Mongodb data will be shown fromone collection only.

{

_id: POST_IDtitle: 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,like: LIKES

},{

user:'COMMENT_BY',message: TEXT,dateCreated: DATE_TIME,like: LIKES

}]

}

Data Modeling Example in RDBMS and MongoDB


RDBMS MongoDB

Database Database

Table Collection

Tuple/Row Document

Column/Attribute/Variable Field

Table Join Embedded Documents

Database Server and Client

Primary KeyPrimary Key (Default key _id provided by mongodbitself)

Mysqld/Oracle mongod

mysql/sqlplus mongo

RDBMS Terminology with MongoDB

Slide 20Slide 20 www.edureka.co/mongodb

MongoDB Production Overview

app server app server app serverapp server

Mongos Mongos Mongos Config 1Config 2

Config 3

mongod

mongod

mongod

Shard1

mongod

mongod

mongod

Shard2

mongod

mongod

mongod

Shard3

mongod

mongod

mongod

Shard4

mongod

mongod

mongod

Shard5

mongod

mongod

mongod

Shard6

Query Router

Read/Write Operations

MongoDB Cluster


MongoDB CRUD Introduction

MongoDB provides rich functionalities for reading and manipulating data.

CRUD stands for Create, Read, Update and Delete. These terms are the basic stuffs for all interactions with the databases.C

R

U

D

Create

Read

Update

Delete


Database Operations

Data Operations

Query

Read Create Update Delete

Data Modification


Demo On Mongo DB

www.edureka.co/mongodb

LIVE Online Class

Class Recording in LMS

24/7 Post Class Support

Module Wise Quiz

Project Work

Verifiable Certificate

Course Features


Questions


MongoDB Course Structure

Module 1

» Design Goals, Architecture and Installation

Module 2

» CRUD Operations

Module 3

» Schema Design and Data Modelling

Module 4

» Administration

Module 5

» Scalability and Availability

Module 6

» Indexing and Aggregation Framework

Module 7

» Application Engineering and MongoDB Tools

Module 8

» Project, Additional Concepts and Case Studies

Build Application With MongoDB

Technology

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