Mongo DB

MongoDB is a document-oriented database. Instead of storing your data in tables made out of individual rows, like a relational database does, it stores your data in collections made out of individual documents.

MongoDB is a fast becoming industry level trends and is gaining most popularity for its powerful query language and its easy to transition from relational database and to NoSQL database. With increasing implementation of Big Data technologies, it is a natural progression for the organizations to look for MongoDB skills.

According to a report by Allied Market Research, the growing awareness of the benefits of NoSQL over RDBMS has resulted in increased demand for MongoDB skills, especially in sectors like, social networks, retail and e-commerce.

Overview

MongoDB is a cross-platform, document oriented database that provides, high performance, high availability, and easy scalability. MongoDB works on concept of collection and document.

Database is a physical container for collections. Each database gets its own set of files on the file system. A single MongoDB server typically has multiple databases.

Collection is a group of MongoDB documents. It is the equivalent of an RDBMS table. A collection exists within a single database. Collections do not enforce a schema. Documents within a collection can have different fields. Typically, all documents in a collection are of similar or related purpose.

A document is a set of key-value pairs. Documents have dynamic schema. Dynamic schema means that documents in the same collection do not need to have the same set of fields or structure, and common fields in a collection's documents may hold different types of data.

Any relational database has a typical schema design that shows number of tables and the relationship between these tables. While in MongoDB, there is no concept of relationship.

Data in MongoDB has a flexible schema.documents in the same collection. They do not need to have the same set of fields or structure, and common fields in a collection’s documents may hold different types of data.

Advantages of MongoDB over RDBMS

 

  • Schema less − MongoDB is a document database in which one collection holds different documents. Number of fields, content and size of the document can differ from one document to another.
  • Structure of a single object is clear.
  • No complex joins.
  • Deep query-ability. MongoDB supports dynamic queries on documents using a document-based query language that's nearly as powerful as SQL.
  • Ease of scale-out − MongoDB is easy to scale.
  • Conversion/mapping of application objects to database objects not needed.
  • Uses internal memory for storing the (windowed) working set, enabling faster access of data.

 

Why Use MongoDB?

  • Document Oriented Storage − Data is stored in the form of JSON style documents.
  • Index on any attribute
  • Replication and high availability
  • Auto-sharding
  • Rich queries
  • Fast in-place updates
  • Professional support by MongoDB
  • Prerequisites

    Before proceeding with this tutorial, you should have a basic understanding of database, text editor and execution of programs, etc. Because we are going to develop high performance database, so it will be good if you have an understanding on the basic concepts of Database (RDBMS).

Course Features

Industry professionals as Trainers

  • Well researched advanced course content created by Industry professionals
  • Assignments
  • Live web design project
  • Technical HR Interview preparations
  • Exam and Industry recognised Certificate

Course Syllabus

Getting Started
    • Important - Download These First - Working Files
    • Setting up for the Course
    • How to Access Your Working Files
Introduction to Mongo DB
    • What Is Meant By Mongo DB?
    • Why Use Mongo DB?
    • Common Terms in Mongo DB
    • Important Features in Mongo DB
Installation and Configuration
    • General Considerations
    • Installing Mongo DB on Windows
    • Installing Mongo DB on A Mac
    • Installing Mongo DB on Debian or Ubuntu Linux
    • Installing Mongo DB on Redhat, Centos or Fedora Linux
    • Drivers - Javascript, Python and Ruby
    • Drivers - Java, Php, Perl and Others
    • Management Tools
    • Mongo DB Configuration, Import and Export
    • Using the Mongo Built-In Javascript Shell - Access, Insert and Find
    • Using the Mongo Built-In Javascript Shell - Update, Remove and Functions
Create, Read, Update and Delete Operations
    • Performing Queries – Overview
    • Performing Queries – Using the Cursor
    • Performing Queries – Query Modifications
    • Adding Information – Database, Collection and Document
    • Adding Information – Arrays
    • Adding Information – Objects
    • Adding Information – The _Id Field
    • Performing Modifications – Basic Document Updates
    • Performing Modifications – Updating Arrays and Fields
    • Performing Modifications – Deleting Documents
Aggregation in MongoDB
Mapreduce in MongoDB
Data Modelling
    • One to One Relationships: Overview
    • One to One Relationships: Manual Approach
    • One to One Relationships: Embedded Approach
    • One to One Relationships: Dbref Approach
    • One to Many Relationships: Overview
    • One to Many Relationships: Normalized Approach
    • One to Many Relationships: Embedded Approach
    • One to Many Relationships: Dbref Approach
Indexes in MongoDB
    • Checking the Query Performance
    • Profiling and Query explain
    • Optimizing query techniques.
    • Indexes in MongoDB
    • Discussing types of Indexes in MongoDB.
Other
    • Introduction to replication
    • Introduction to sharding
    • Introduction to GridFS
    • Zookeeper operationsSmall project to show practical Implementation of above concepts

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