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MongoDBEr. Shiva K. ShresthaME Computer, NCITDistributed Operating System

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2Introduction

MongoDB = “Humongous DB”Open-source & Cross-platformDocument-based“High Performance, High Availability”Automatic Scaling

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3Database EvolutionFlat Files RDBMS NoSQL MongoDB1970s: data stored in flat file system

1979: a standard way of query the data - what do we want to query,how to process that query but

1998:1. Key-value Store2. Tabular3. Document oriented (MongoDB, CouchDB, etc.)

2009: Free & Open Source, Cross-Platform, Document Oriented

Problem:no standard implementation

Problem: with the big n huge amount data

Problem: Less support for Complex Queries

Solution: Relational Database

Solution: NoSQL Solution: Use Third-Party GUIs

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4Features Expressive Query Language & Secondary Indexes Strong Consistency Flexibility Scalability & Performance

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General Purpose

MongoDB is:

Easy to Use

Fast & Scalable

Sophisticated query language

Full featured indexesRich 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 downtimeAuto-sharding built

inOperates at in-memory speed

wherever possible

6Comparisons RDBMS MongoDBRelational database Document-oriented database, non

relational

Schema based database, follow joins Schema-less database, references and $lookup

Data stored in tables (tables contain collection of rows)

Data stored in form of collection (collection contain group of object document)

No horizontal scalingEg. 1st row has 5 column then 2nd row must have 5 column for the given table

Horizontal scalingEg. 1st row has 5 column then 2nd row can have any no of column for the given table

SQL queries are used JSON, BSON format

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7Data FormatJSON XML{"employees“ :[{"firstName":“Anju", "lastName":“Shah"},{"firstName":“Sumit Kumar", "lastName":“Shah"},{"firstName":“Shiva K.", "lastName":“Shrestha"}]}

<employees> <employee> <firstName>Anju</firstName> <lastName>Shah</lastName> </employee> <employee> <firstName>Sumit Kumar</firstName> <lastName>Shah</lastName> </employee> <employee> <firstName>Shiva K.</firstName> <lastName>Shrestha</lastName> </employee> </employees>

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8Advantages Schema less Structure of single object is clear No complex joins Document-based Query language Conversion/Mapping is not needed Use internal memory, hence faster

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9Why and Where to use Object oriented storage style (JSON) Index on any attributes Replication and Availability Auto-sharding

Big data Content management system Mobile and social infrastructure Data Hub

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10Terminology Translation6/20/2016

SQL Terms/Concepts MongoDB Terms/ConceptsDatabase DatabaseTable CollectionRow Document or BSON documentColumn FieldIndex IndexTable joins Embedded documents & linkingUnique column or column combination as primary key.

Primary key is automatically set to the _id field.

Aggregation (e.g. group by) Aggregation pipeline

11CRUD OperationsInsertion:

Update:

Delete:

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SQL MongoDB CommandINSERT INTO t (fn, ln) VALUES (‘Saroj', ‘Shakya') db.t.insert({fn:‘Saroj', ln: ‘Shakya'})

SQL MongoDB CommandUPDATE t SET ln='Nepal' WHERE ln='Shakya'

db.t.update({ln:‘Shakya'},{$set:{ln:‘Nepal'}})

SQL MongoDB CommandDELETE FROM t WHERE fn=‘Saroj' db.t.remove({fn:‘Saroj'})

12Retrieving Data6/20/2016

SQL Statement MongoDB CommandsSELECT * FROM table

db.collection.find()

SELECT * FROM tableWHERE artist = ‘Rekha’

db.collection.find({Artist:”Rekha”})

SELECT*FROM tableORDER BY Title

db.collection.find().sort(Title:1)

DISTINCT .distinct()GROUP BY .group()>=, < $gte, $lt

13Replication6/20/2016

14Knee Curve6/20/2016

15Drivers & Frameworks

Morphia

MEAN Stack

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16Conclusions MongoDB is fast

Very little CPU overhead Implemented in C++ for best performance

Free & Open Source, Cross-Platform, Document Oriented Easier and faster integration of data Very rapid development

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17

Thank You!

Q/A Session:6/20/2016