This document provides an agenda for introducing MongoDB. It discusses how MongoDB is a general purpose, document-oriented database that is easy to use, fast, scalable, and supports sophisticated queries and indexing. It compares MongoDB to relational databases and how MongoDB supports a dynamic schema and embedding of documents.

1. Open source, high performance
Document-oriented database

2. • Introduction to MongoDB
• MongoDB Rationale
• MongoDB Relative to RDBMS
• MongoDB- Schemaless
• Web Application Framework with MongoDB
• JSON
• Introduction to Mongo Shell
• CRUD
• Further Readings
Agenda

3. General
Purpose
Introduction to MongoDB
Easy to
Use
Fast &
Scalable
Sophisticated
query language
Full featured
indexes
Rich data model
Simple to setup
and manage
Native language
drivers in all
popular languages
Easy mapping to
object oriented
code
Dynamically add /
remove capacity
with no downtime
Auto-sharding
built in
Operates at in-
memory speed
wherever possible

4. • MongoDB was created to make
it easy to code, scale, and manage databases.
• In agile programming, the sprint cycles are usually 3-5
weeks long.
• Adding new columns to same collection is easy and
intuitive.
Agile and Scalable

5. MongoDB is fast and scalable
Better data locality
Relational MongoDB
In-Memory
Caching
Distributed Architecture
Horizontal Scaling
Replication/HA

6. • Scaling horizontally (scale out) over commodity hardware is
cheaper
• RDBMS best features should be support:
– Ad hoc queries
– Fully featured indexes
– Secondary indexes
• Avoid things which does not scale well horizontally:
– Long running multi-row transactions
– Joins
• Schema less design:
– support for heterogeneous data within same collection
– No more configuring database columns with types
• Make web programming simpler and more productive by
support of APIs.
MongoDB Rationale

7. • Collection vs table
• Document vs row
• Field vs column
• schema-less vs schema-oriented
• Embedded documents, linking vs Joins
MongoDB Relative to RDBMS

8. Features MySQL MongoDB
Rich Data Model No Yes
Dynamic Schema No Yes
Typed Data Yes Yes
Data Locality No Yes
Field Updates Yes Yes
Easy for Programmers No Yes
Complex Transactions Yes No
Auditing Yes Yes
Auto-Sharding No Yes
MySQL vs MongoDB

9. • MongoDB does not need any pre-defined data schema
• Every document could have different data!
MongoDB- Schema less
name: “Kartik”,
color: “Red”,
loc: [40.7, 73.4],
Hobbies: “cycling”}
{name: “Avinash”,
aliases: [“Avi”]}
name: “Ram”,
HasHat: ”yes”}
{name: “Manish”,
Food: “Pasta”,
height: 172,
loc: [44.6, 71.3]}
{name: “Rajesh,
color: “blue”,
birthplace: “NY”,
aliases: [“Raj”,
“limbo”],
loc: [32.7, 63.4]}

10. Web Application Framework with
MongDB
MongoDB
Mongod
process
Mongo
Shell
JavaScript Interpreter
TCP/IP
Java App Code
MVC
MongoDB Java
Driver
JVM
User Request Rest API
TCP/IP
Json

11. • JSON (JavaScript Object Notation) is a lightweight data-
interchange format.
• It is easy for humans to read and write.
• It is easy for machines to parse and generate.
• It is based on a subset of the JavaScript Programming
Language.
• JSON is a text format that is completely language independent
but uses conventions that are familiar to programmers of the
C-family of languages, including C, C++, C#, Java, JavaScript,
Perl, Python, and many others.
• These properties make JSON an ideal data-interchange
language.
JSON

12. • Quick Demo on use to Mongo Shell
• Demonstration of how to start the Mongod process
• Connecting to MongoDB via mongo
• Basics commands
Introduction to Mongo Shell

13. • db.collection.insert()
• db.collection.find()/ db.collection.findOne()
• db.collection.update({string:value},{$set:{string:value}})
• db.collection.remove()
CRUD

14. • MongoDB is open source and there is no cost to
download and use it. 
• MongoDB is a general purpose database that is used for
a variety of use cases. The most common use cases for
MongoDB include:
– Single View,
– Internet of Things,
– Mobile,
– Real-Time Analytics,
– Catalog, and
– Content Management.
• https://university.mongodb.com/
• http://docs.mongodb.org/manual/reference/sql-
comparison/
• http://docs.mongodb.org/manual/reference/sql-
aggregation-comparison/
Further Readings