MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling.
In simple words, you can say that – Mongo DB is a document-oriented database. It is an open-source product, developed and supported by a company named 10gen.
MongoDB is available under General Public license for free, and it is also available under Commercial license from the manufacturer.
The manufacturing company 10gen has defined MongoDB as:
“MongoDB is a scalable, open source, high performance, document-oriented database.” – 10gen
MongoDB was designed to work with commodity servers. Now it is used by the company of all sizes, across all industry.

History of MongoDB

The initial development of MongoDB began in 2007 when the company was building a platform as a service similar to window azure.
Window azure is a cloud computing platform and infrastructure, created by Microsoft, to build, deploy and manage applications and service through a global network.
MongoDB was developed by a NewYork based organization named 10gen which is now known as MongoDB Inc. It was initially developed as a PAAS (Platform as a Service). Later in 2009, it is introduced in the market as an open source database server that was maintained and supported by MongoDB Inc.
The first ready production of MongoDB 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 January 10, 2014.

Purpose of building MongoDB

It may be a very genuine question that – “what was the need of MongoDB although there were many databases in action?”
There is a simple answer:
All the modern applications require big data, fast features development, flexible deployment, and the older database systems not competent enough, so the MongoDB was needed.
The primary purpose of building MongoDB is:
• Scalability
• Performance
• High Availability
• Scaling from single server deployments to large, complex multi-site architectures.
• Key points of MongoDB
• Develop Faster
• Deploy Easier
• Scale Bigger
First of all, we should know what is document-oriented database?
Example of document-oriented database
MongoDB is a document-oriented database. It is a key feature of MongoDB. It offers a document-oriented storage. It is very simple you can program it easily.
MongoDB stores data as documents, so it is known as document-oriented database.
1. FirstName = “John”,
2. Address = “Detroit”,
3. Spouse = [{Name: “Angela”}].
4. FirstName =”John”,
5. Address = “Wick”
There are two different documents (separated by “.”).
Storing data in this manner is called as document-oriented database.
Mongo DB falls into a class of databases that calls Document Oriented Databases. There is also a broad category of database known as No SQL Databases.

Features of MongoDB

These are some important features of MongoDB:
1. Support ad hoc queries
In MongoDB, you can search by field, range query and it also supports regular expression searches.
2. Indexing
You can index any field in a document.
3. Replication
MongoDB supports Master Slave replication.
A master can perform Reads and Writes and a Slave copies data from the master and can only be used for reads or back up (not writes)
4. Duplication of data
MongoDB can run over multiple servers. The data is duplicated to keep the system up and also keep its running condition in case of hardware failure.
5. Load balancing
It has an automatic load balancing configuration because of data placed in shards.
6. Supports map reduce and aggregation tools.
7. Uses JavaScript instead of Procedures.
8. It is a schema-less database written in C++.
9. Provides high performance.
10. Stores files of any size easily without complicating your stack.
11. Easy to administer in the case of failures.
12. It also supports:
JSON data model with dynamic schemas
Auto-sharding for horizontal scalability
Built in replication for high availability
Now a day many companies using MongoDB to create new types of applications, improve performance and availability.
So, this brings us to the end of blog. This Tecklearn ‘Overview of MongoDB, it’s history and purpose of building 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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