Most Popular Big Data and Data Analytics trends of 2018 – Mongo DB


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Most popular Database of today-A snippet on what is MongoDB

Mongo DB is one of the most popular and sought after database technologies in the market at the moment. It is an open source document oriented nosql database that is widely used by increasingly many corporations across all domains. For this reason, if you search for “mongodb salary” in google, you will find some very good numbers. This mongodb tutorial focuses on features of mongodb and specifics would be covered in later posts.

About MongoDB Inc

Founded in 2007 by Dwight Merriman, Eliot Horowitz and Kevin Ryan. Mongodb proved to be one of the hottest nosql open source database technologies trending in the current market with 30 million downloads already spanning across 19 countries with a talent pool of over 1000 employees. It is one of the fastest growing database technologies in the current market.

Target Audience

Students and professionals that are focused on learning about Mongo database.


Image Courtesy: Garrett Heath@Flickr

What is MongoDB

A record in Mongo DB is a document.

The document is a data structure comprising of field and value pairs. These documents are similar to JSON objects. The values of fields can be other documents, arrays and arrays of documents.

mongodb json

Image Courtesy: Linux Screenshots@Flickr

Fast facts on mongodb stocks:

Mongodb stock has skyrocketed in the last one year from 32.07 USD to 84.01 USD. This shows the ever growing demand for mongodb.

mongodb stock

Image Courtesy: google

How to create Mongodb document


name:    “adam”,                           <--- field: value

age:  32,                                  <---- field: value

status: “B”,                               <--- field: value

groups: [ “news”, “sports” ]               <--- field: value


Advantages of using Mongodb documents

  • Documents (i.e Objects) resemble native data types as in many programming languages.
  • Embedded documents and arrays lessen the use of complex joins to achieve the result sets.
  • Dynamic schema supports fluent polymorphism.

Key Features:

High Performance Data Persistence

  • Embedded data models reduce significant I/O on the database.
  • Queries run faster using indexes. They can include keys from embedded documents and arrays.

Rich Query Language

  • Mongo DB’s rich query language supports read and write (CRUD) operations.
  • The query language also supports Data Aggregation, Text search and Geo-spatial queries.

High Availability

  • Mongo DB’s replication feature is called replica set (group mongodb servers that maintain the same data set providing high availability and data redundancy) which provides automatic failover and data redundancy.

Horizontal Scalability

  • Horizontal scalability is a core functionality of mongodb.
  • Sharding distributes data across a cluster of machines.
  • Mongo db creates zones of data basing on a shard key. In a Balanced cluster, Mongo db directs all reads and writes covered by a zone only to those shards that are inside the zone.

Support for Multiple Storage Engines

Mongo DB supports multiple storage engines such as:

  • WiredTiger Storage Engine and
  • MMAPv1 Storage Engine

Mongo DB also provides pluggable storage engine API that enables third parties to develop customized storage engines for Mongo DB.

You can navigate to mongo wiki for more snippets on Mongodb. You can download mongodb documentation from mongodb university here.

What is Mongodb written in?

Mongodb is written in C++ with extensive suite of tests in Java script.

Contributing to Mongodb

Interestingly, mongodb welcomes contributions from community!

If you are interested, you can make contributions here.

Download mongodb community edition before exploring the cloud options. I will post practicals on mongodb in my next tutorials.

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