Data in MongoDB features a flexible schema. documents within 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 knowledge.

Some considerations while designing Schema in MongoDB

• Design your schema according to user requirements.
• Combine objects into one document if you will use them together. Otherwise separate them (but make sure there should not be need of joins).
• Duplicate the knowledge (but limited) because disk space is cheap as compare to compute time.
• Do joins while write, not on read.
• Optimize your schema for most frequent use cases.
• Do complex aggregation within the schema.
Example
Suppose a client needs a database design for his blog/website and see the differences between RDBMS and MongoDB schema design. Website has the following requirements.
• Every post has the unique title, description and url.
• Every post can have one or more tags.
• Every post has the name of its publisher and total number of likes.
• Every post has comments given by users along with their name, message, data-time and likes.
• On each post, there can be zero or more comments.
Within RDBMS schema, design for above requirements will have minimum three tables.

While within MongoDB schema, design will have one collection post and therefore the following structure −
{
_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,
like: LIKES
},
{
user:’COMMENT_BY’,
message: TEXT,
dateCreated: DATE_TIME,
like: LIKES
}
]
}
So while showing the knowledge, within RDBMS you need to join three tables and within MongoDB, knowledge will be shown from one collection only.

MongoDB – Create Database

In this blog further we will see how to create a database within MongoDB.

The use Command

MongoDB 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
Basic syntax of use DATABASE statement is as follows −
use DATABASE_NAME
Example
If you want to use a database with name <mydb>, then use DATABASE statement would be as follows −
>use mydb
switched to db mydb
To check your currently selected database, use the command db
>db
mydb
If you want to check your databases list, use the command show dbs.
>show dbs
local 0.78125GB
test 0.23012GB
Your created database (mydb) is not present within list. To display database, you need to insert at least one document into it.
>db.movie.insert({“name”:”tecklearn”})
>show dbs
local 0.78125GB
mydb 0.23012GB
test 0.23012GB
In MongoDB default database is test. If you didn’t create any database, then collections will be stored in test database.

MongoDB – Drop Database

We will now see how to drop a database using MongoDB command.

The dropDatabase() Method

MongoDB db.dropDatabase() command is used to drop a existing database.
Syntax
Basic syntax of dropDatabase() command is as follows −
db.dropDatabase()
This will delete the selected database. If you have not selected any database, then it will delete default ‘test’ database.
Example
First, check the list of available databases by using the command, show dbs.
>show dbs
local 0.78125GB
mydb 0.23012GB
test 0.23012GB
>
If you want to delete new database <mydb>, then dropDatabase() command would be as follows −
>use mydb
switched to db mydb
>db.dropDatabase()
>{ “dropped” : “mydb”, “ok” : 1 }
>
Now check list of databases.
>show dbs
local 0.78125GB
test 0.23012GB
>
So, this brings us to the end of blog. This Tecklearn ‘Data Modelling in MongoDB and How to create Database in MongoDB’ helps you with commonly asked questions if you are looking out for a job in MongoDB and No-SQL Database Domain.
If you wish to learn and build a career in MongoDB or No-SQL Database domain, then check out our interactive, MongoDB Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

MongoDB Training

MongoDB Training

About the Course

Tecklearn’s MongoDB Training helps you to master the NoSQL database. The course makes you job-ready by letting you comprehend schema design, data modelling, replication, and query with MongoDB through real-time examples. Along with this, you’ll also gain hands-on expertise in installing, configuring, and maintaining the MongoDB environment, including monitoring and operational strategies from this online MongoDB training. Upon completion of this online training, you will hold a solid understanding and hands-on experience with MongoDB.

Why Should you take MongoDB Training?

• MongoDB – a $36 billion to a $40 billion market growing at 8% to 9% annually – Forbes.com
• Average salary of a Mongo DB certified professional is $134k – Indeed.com
• MongoDB has more than 900 customers, including 27 Fortune 100 companies like Cisco, eBay, eHarmony, MetLife & Salesforce.com

What you will Learn in this Course?

Introduction to MongoDB and Importance of NoSQL
• Understanding the basic concepts of RDBMS
• What is NoSQL Database and its significance?
• Challenges of RDBMS and How NoSQL suits Big Data needs
• Types of NoSQL Database and NoSQL vs. SQL Comparison
• CAP Theorem and Implementing NoSQL
• Introduction to MongoDB and its advantages
• Design Goals for MongoDB Server and Database, MongoDB tools
• Collection, Documents and Key Value Pair
• Introduction to JSON and BSON documents
• MongoDB installation
MongoDB Installation
• MongoDB Installation
• Basic MongoDB commands and operations,
• Mongo Chef (MongoGUI) Installation
Schema Design and Data Modelling
• Why Data Modelling?
• Data Modelling Approach
• Data Modelling Concepts
• Difference between MongoDB and RDBMS modelling
• Challenges for Data Modelling
• Model Relationships between Documents
• Data Model Examples and Patterns
• Model Tree Structures
CRUD Operations
• MongoDB Architecture
• CRUD Introduction and MongoDB CRUD Concepts
• MongoDB CRUD Concerns (Read and Write Operations)
• Cursor Query Optimizations and Query Behaviour in MongoDB
• Distributed Read and Write Queries
• MongoDB Datatypes
Indexing and Aggregation Framework
• Concepts of Data aggregation and types and data indexing concepts
• Introduction to Aggregation
• Approach to Aggregation
• Types of Aggregation: Pipeline, MapReduce and Single Purpose
• Performance Tuning
MongoDB Administration
• Administration concepts in MongoDB
• MongoDB Administration activities: Health check, recovery, backup, database sharing and profiling, performance tuning etc.
• Backup and Recovery Methods for MongoDB
• Export and Import of Data from MongoDB
• Run time configuration of MongoDB
MongoDB Security
• Security Introduction
• MongoDB security Concepts and security approach
• MongoDB integration with Java and Robomongo
Got a question for us? Please mention it in the comments section and we will get back to you.

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