1. MongoDB Introduction, Installation & Execution
By Prof. B.A.Khivsara
Note: The material to prepare this presentation has been taken from internet and are generated only for students reference and not for commercial use.

2. Outline Difference Between SQL and NoSQL
Study of Open Source NOSQL Database
MongoDB Installation,
Basic CRUD operations,
Execution

3. Difference Between SQL and NoSQL
SQL Databases
SQL Standard
SQL Characteristics
SQL Database Examples
NoSQL Databases
NoSQL Defintion
General Characteristics
NoSQL Database Types
NoSQL Database Examples
12 November 2018

4. SQL Characteristics Data stored in tables
Relationships represented by data
Data Manipulation Language
Data Definition Language
Transactions
Abstraction from physical layer
12 November 2018

5. Data Definition Language
Schema defined at the start
Create Table
Constraints to define and enforce relationships
Primary Key
Foreign Key
Etc.
Triggers to respond to Insert, Update , & Delete
Stored Modules
Alter …
Drop …
Security and Access Control
12 November 2018

6. Data Manipulation Language (DML)
Data manipulated with Select, Insert, Update, & Delete
Data Aggregation
Compound statements
Functions and Procedures
Explicit transaction control
12 November 2018

7. Transactions – ACID Properties
Atomic – All of the work in a transaction completes (commit) or none of it completes
Consistent – A transaction transforms the database from one consistent state to another consistent state. Consistency is defined in terms of constraints.
Isolated – The results of any changes made during a transaction are not visible until the transaction has committed.
Durable – The results of a committed transaction survive failures
12 November 2018

8. Significant portions of the world’s economy use SQL databases!
SQL Database Examples
Commercial
IBM DB2
Oracle RDMS
Microsoft SQL Server
Sybase SQL Anywhere
Open Source (with commercial options)
MySQL
Ingres
Significant portions of the world’s economy use SQL databases!
12 November 2018

9. NoSQL Definition- From www.nosql-database.org
Next Generation Databases mostly addressing some of the points:
non-relational,
distributed, 
open-source and
horizontal scalable.
Often more characteristics apply as:
schema-free,
easy replication support,
simple API,
eventually consistent / BASE (not ACID),
huge data amount, and more.
12 November 2018

10. NoSQL Products/Projects
lists 122 NoSQL Databases
Cassandra
CouchDB
Hadoop & Hbase
MongoDB
StupidDB
Etc.
12 November 2018

11. NoSQL Distinguishing Characteristics
Large data volumes
Google’s “big data”
Scalable replication and distribution
Potentially thousands of machines
Potentially distributed around the world
Queries need to return answers quickly
Schema-less
ACID transaction properties are not needed – BASE
CAP Theorem
Open source development
12 November 2018

12. BASE Transactions Acronym contrived to be the opposite of ACID
Basically Available,
Soft state,
Eventually Consistent
Characteristics
Weak consistency – stale data OK
Availability first
Best effort
Approximate answers OK
Aggressive (optimistic)
Simpler and faster
12 November 2018

13. Brewer’s CAP Theorem CAP Theorem Consistency Availability
Partition tolerance
12 November 2018

14. Consistency all nodes see the same data at the same time – Wikipedia
client perceives that a set of operations has occurred all at once – Pritchett
More like Atomic in ACID transaction properties
12 November 2018

15. Availability
node failures do not prevent survivors from continuing to operate – Wikipedia
Every operation must terminate in an intended response – Pritchett
12 November 2018

16. Partition Tolerance
the system continues to operate despite arbitrary message loss – Wikipedia
Operations will complete, even if individual components are unavailable – Pritchett
12 November 2018

17. Outline Difference Between SQL and NoSQL
Study of Open Source NOSQL Database
MongoDB Installation,
Basic CRUD operations,
Execution

18. Open Source Small upfront software costs
Suitable for large scale distribution on commodity hardware
12 November 2018

19. NoSQL Database Types Column Store –
Each storage block contains data from only one column
Document Store – stores documents made up of tagged elements
Key-Value Store – Hash table of keys
12 November 2018

20. Other Non-SQL Databases
XML Databases
Graph Databases
Codasyl Databases
Object Oriented Databases
Etc…
12 November 2018

21. NoSQL Example: Column Store
Each storage block contains data from only one column
Example: Hadoop/Hbase
Yahoo, Facebook
Example: Ingres VectorWise
Column Store integrated with an SQL database
12 November 2018

22. Column Store Comments More efficient than row (or document) store if:
Multiple row/record/documents are inserted at the same time so updates of column blocks can be aggregated
Retrievals access only some of the columns in a row/record/document
12 November 2018

23. NoSQL Examples: Key-Value Store
Hash tables of Keys
Values stored with Keys
Fast access to small data values
Example – Project-Voldemort
Linkedin
Example – MemCacheDB
Backend storage is Berkeley-DB
12 November 2018

24. Map Reduce Technique for indexing and searching large data volumes
Two Phases, Map and Reduce
Map
Extract sets of Key-Value pairs from underlying data
Potentially in Parallel on multiple machines
Reduce
Merge and sort sets of Key-Value pairs
Results may be useful for other searches
12 November 2018

25. Map Reduce Patent Google granted US Patent 7,650,331, January 2010
System and method for efficient large-scale data processing A large-scale data processing system and method includes one or more application-independent map modules configured to read input data and to apply at least one application-specific map operation to the input data to produce intermediate data values, wherein the map operation is automatically parallelized across multiple processors in the parallel processing environment. A plurality of intermediate data structures are used to store the intermediate data values. One or more application-independent reduce modules are configured to retrieve the intermediate data values and to apply at least one application-specific reduce operation to the intermediate data values to provide output data.
12 November 2018

26. NoSQL Example: Document Store
Example: CouchDB
BBC
Example: MongoDB
Foursquare, Shutterfly
JSON – JavaScript Object Notation
12 November 2018

27. CouchDB JSON Example
{ "_id": "guid goes here", "_rev": "314159", "type": "abstract", "author": "Keith W. Hare" "title": "SQL Standard and NoSQL Databases", "body": "NoSQL databases (either no-SQL or Not Only SQL) are currently a hot topic in some parts of computing.", "creation_timestamp": "2011/05/10 13:30: " }
12 November 2018

28. CouchDB JSON Tags "_id" "_rev" "type", "author", "title", etc.
GUID – Global Unique Identifier
Passed in or generated by CouchDB
"_rev"
Revision number
Versioning mechanism
"type", "author", "title", etc.
Arbitrary tags
Schema-less
Could be validated after the fact by user-written routine
12 November 2018

29. MongoDB

30. What is MongoDB ?
• Scalable High-Performance Open-source, Document-orientated database.
• Built for Speed
• Rich Document based queries for Easy readability.
• Full Index Support for High Performance.
• Replication and Failover for High Availability.
• Auto Sharding for Easy Scalability.
• Map / Reduce for Aggregation.

31. Why use MongoDB? • SQL was invented in the 70’s to store data.
• MongoDB stores documents (or) objects.
• Now-a-days, everyone works with objects (Python/Ruby/Java/etc.)
• And we need Databases to persist our objects. Then why not store objects directly ?
• Embedded documents and arrays reduce need for joins. No Joins and No-multi document transactions.

32. What is MongoDB great for?
• RDBMS replacement for Web Applications.
• Semi-structured Content Management.
• Real-time Analytics & High-Speed Logging.
• Caching and High Scalability
Web 2.0, Media, SAAS, Gaming
HealthCare, Finance, Telecom, Government

33. Some Companies using MongoDB in Production
Not great for?
• Highly Transactional Applications.
• Problems requiring SQL.
Some Companies using MongoDB in Production

34. Advantages of MongoDB
Schema less : Number of fields, content and size of the document can be differ from one document to another.
No complex joins
Data is stored as JSON style
Index on any attribute
Replication and High availability

35. MongoDB Terminologies for RDBMS concepts
Database
Table, View
Collection
Row
Document (JSON, BSON)
Column
Field
Index
Join
Embedded Document
Foreign Key
Reference
Partition
Shard
Javascript

36. JSON “JavaScript Object Notation”
Easy for humans to write/read, easy for computers to parse/generate
Objects can be nested
Built on
name/value pairs
Ordered list of values

37. BSON “Binary JSON” Binary-encoded serialization of JSON-like docs
Embedded structure reduces need for joins
Goals
Lightweight
Traversable
Efficient (decoding and encoding)

38. BSON Example { "_id" : "37010" “City" : “Nashik", “Pin" : 423201,
"state" : “MH",
“Postman” : {
name: “Ramesh Jadhav”
address: “Panchavati” }

39. Data Types of MongoDB Integer Boolean Date Binary data Double
String
Arrays
Null
Object ID
Binary data
Date

40. Data Types
String : This is most commonly used datatype to store the data. String in mongodb must be UTF-8 valid.
Integer : This type is used to store a numerical value. Integer can be 32 bit or 64 bit depending upon your server.
Boolean : This type is used to store a boolean (true/ false) value.
Double : This type is used to store floating point values.
Min/ Max keys : This type is used to compare a value against the lowest and highest BSON elements.
Arrays : This type is used to store arrays or list or multiple values into one key.
Timestamp : ctimestamp. This can be handy for recording when a document has been modified or added.
Object : This datatype is used for embedded documents.

41. Data Types Null : This type is used to store a Null value.
Symbol : This datatype is used identically to a string however, it's generally reserved for languages that use a specific symbol type.
Date : This datatype is used to store the current date or time in UNIX time format. You can specify your own date time by creating object of Date and passing day, month, year into it.
Object ID : This datatype is used to store the document’s ID.
Binary data : This datatype is used to store binay data.
Code : This datatype is used to store javascript code into document.
Regular expression : This datatype is used to store regular expression

42. Outline Difference Between SQL and NoSQL
Study of Open Source NOSQL Database
MongoDB Installation,
Basic CRUD operations,
Execution

43. Find version of Windows
enter the following commands in the Command Prompt or Powershell:
wmic os get caption
wmic os get osarchitecture

44. Installation in Windows
Download MongoDB from Website:
Select option
Windows
Download and Run

45. Starting MongoDB in Windows
Create one folder (eg SNJB) in bin folder of MongoDB
Goto command prompt
Goto bin dir of MongoDB and write following command
mongod --storageEngine=mmapv1 --dbpath SNJB
(Server will started and listen at port)
Open another command prompt and give command mongo
(Client will be started)

46. Installation in Ubuntu
Download MongoDB from Website:
Select option
Linux
Download and Run

47. Starting MongoDB in Ubuntu
Create a folder in bin directory of mongodb
Open terminal
Goto mongodb bin folder (cd mongo….)
Type ./mongod (Server is started)
Open another terminal
Type ./mongo (client will be started)
Run all commands on client terminal

48. Outline Difference Between SQL and NoSQL
Study of Open Source NOSQL Database
MongoDB Installation,
Basic CRUD operations,
Execution

49. Basic Database Operations
collection

50. Basic Database Operations- Database
switched to database provided with ciommand
use <database name>
To check currently selected database use the command db db
Displays the list of databases
show dbs
To Drop the database
db.dropDatabase()

51. Basic Database Operations- Collection
To create collection
db.createCollection (name)
Ex:- db.createCollection(Stud)
List out all names of collection in current database
>show collections
In mongodb you don't need to create collection. MongoDB creates collection automatically, when you insert some document.
db.databasename.insert
({Key : Value})
Ex:- db.Stud.insert({{Name:”Jiya”})
MongoDB's db.collection.drop() is used to drop a collection from the database.
db.collection.drop() Example:- db.Stud.drop()

52. CRUD Operations
Insert
Find
Update
Delete

53. References https://docs.mongodb.com/manual/introduction/