Databases are often divided in 3 types:
1. RDBMS (Relational Database Management System)
2. OLAP (Online Analytical Processing)
3. NoSQL (recently developed database)

NoSQL Database

NoSQL Database is employed to refer a non-SQL or non-relational database.
It provides a mechanism for storage and retrieval of data other than tabular relations model employed in relational databases. NoSQL database doesn’t use tables for storing data. It is generally employed to store big data and real-time web applications.

History behind the creation of NoSQL Databases

In the early 1970, Flat File Systems are employed. Data were stored in flat files and the biggest problems with flat files are each company implement their own flat files and there are no standards. It is very difficult to store data in the files, retrieve data from files because there’s no standard way to store data.
Then the relational database was created by E.F. Codd and these databases answered the question of having no standard way to store data. But later relational database also gets a problem that it could not handle big data, due to this problem there was a need of database which can handle every types of problems then NoSQL database was developed.

Advantages of NoSQL

• It supports query language.
• It provides fast performance.
• It provides horizontal scalability.

MongoDB advantages over RDBMS

In recent days, MongoDB is a new and popularly employed database. It is a document based, non-relational database provider.
Although it is 100 times faster than the traditional database but it is early to mention that it will broadly replace the traditional RDBMS. But it may be very useful in term to realize performance and scalability.
A 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.

MongoDB Advantages

• MongoDB is schema less. It is a document database in which one collection holds different documents.
• There could also be difference between number of fields, content and size of the document from one to other.
• Structure of a single object is clear in MongoDB.
• There are not many complex joins in MongoDB.
• MongoDB provides the facility of deep query because it supports a powerful dynamic query on documents.
• It is extremely easy to scale.
• It uses internal memory for storing working sets and this is often the reason of its fast access.

Distinctive features of MongoDB

• Easy to use
• Light Weight
• Extremely faster than RDBMS

Where MongoDB should be employed

• Big and complex data
• Mobile and social infrastructure
• Content management and delivery
• User data management
• Data hub

Performance analysis of MongoDB and RDBMS

• In relational database (RDBMS) tables are using as storing elements, while in MongoDB collection is employed.
• In the RDBMS, we have multiple schemas and, in each schema, we create tables to store data while, MongoDB is a document-oriented database in which data is written in BSON format which is a JSON like format.
• MongoDB is almost 100 times faster than traditional database systems.

MongoDB Datatypes

Following is a list of usable data types in MongoDB.

Data Types	Description
String	String is the most ordinarilly employed datatype. It is employed to store data. A string must be UTF 8 valid in mongodb.
Integer	Integer is employed to store the numeric value. It can be 32 bit or 64 bit depending on the server you are using.
Boolean	This datatype is employed to store boolean values. It just shows YES/NO values.
Double	Double datatype stores floating point values.
Min/Max Keys	This datatype compares a value against the lowest and highest bson elements.
Arrays	This datatype is employed to store a list or multiple values into a one key.
Object	Object datatype is employed for embedded documents.
Null	It is employed to store null values.
Symbol	It is generally employed for languages that use a specific type.
Date	This datatype stores the present date or time in unix time format. It causes you possible to specify your own date time by creating object of date and pass the worth of date, month, year into it.

So, this brings us to the end of blog. This Tecklearn ‘Understand NoSQL Databases and MongoDB advantages over Relational DBMS’ 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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