why nosql and mongodb for big data

8
Why NoSQL

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Post on 25-May-2015

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DESCRIPTION

This ingite length deck talks about why we have seen so much database innovation and the genesis of the NoSQL movement over the last 5 year. While there are many great NoSQL products it speaks to why MongoDB is dominating the space and is the heir apparent to the RDBMS for modern operational data.

TRANSCRIPT

Page 1: Why NoSQL and MongoDB for Big Data

Why NoSQL

Page 2: Why NoSQL and MongoDB for Big Data

2

Dawn of Databases to Present

Brewer’s CapbornWWW

born

10genfounded

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

SQLinvented

Oraclefounded

PC’s gaintraction

Client Server

DynamicWeb Content

3 tierarchitecture

Web applications

SOA

CloudComputing

released

NoSQLMovement

BigTable

IDS(network)

IMS(hierarchica

l)

MUMPS

Codd’s paper

IDMS(network)

Page 3: Why NoSQL and MongoDB for Big Data

3

Big Data

Sensor Data (volume, velocity)Situational Awareness (Variety, Volume)

SIGINT(V ) Asset Management (variety, velocity)

OSINT( 3V )

Social Media (

3V )3

Modern Data

Page 4: Why NoSQL and MongoDB for Big Data

4

Relational Database Challenges

Data Types

• Unstructured data

• Semi-structured data

• Polymorphic data

Volume of Data

• Petabytes of data

• Trillions of records

• Millions of queries per second

Agile Development

• Iterative

• Short development cycles

• Changing data model

New Architectures

• Horizontal scaling

• Commodity servers

• Cloud computing

Page 5: Why NoSQL and MongoDB for Big Data

5

The Evolution of Databases

2010

RDBMS

NoSQL

OLAP/BI

Hadoop

2000

RDBMS

OLAP/BI

1990

RDBMS

Operational Data

Datawarehouse

Online

Offline

Page 6: Why NoSQL and MongoDB for Big Data

6

Fully Featured NoSQL

Data Model{ first_name: ‘Paul’, surname: ‘Miller’, city: ‘London’, location: [45.123,47.232], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } }}

Rich Queries• Find Paul’s cars• Find everybody in London with a car

built between 1970 and 1980

Geospatial• Find all of the car owners within 5km of

Trafalgar Sq.

Text Search• Find all the cars described as having

leather seats

Aggregation• Calculate the average value of Paul’s

car collection

Native Indexes• Secondary• Compound• Geospatial

• Full Text• Hash• Covering

Security• Kerberos• FIPS 140-2• Field Level Security

• LDAP• Auditing• RBAC

Page 7: Why NoSQL and MongoDB for Big Data

7

Indeed.com TrendsTop Job Trends

1. HTML 5

2. MongoDB

3. iOS

4. Android

5. Mobile Apps

6. Puppet

7. Hadoop

8. jQuery

9. PaaS

10. Social Media

NoSQL Space

LinkedIn Job Skills

MongoDB

Competitor 1

Competitor 2

Competitor 3

Competitor 4

Competitor 5

All Others

Google Search

MongoDB

Competitor 1

Competitor 2

Competitor 3

Competitor 4

Jaspersoft Big Data Index

Direct Real-Time Downloads

MongoDB

Competitor 1

Competitor 2

Competitor 3

Page 8: Why NoSQL and MongoDB for Big Data

8

Open Source Software

Technology must scale

Cost must scale!