The document discusses MongoDB and its benefits over traditional databases. MongoDB can better handle increasing data volumes and connected devices by adapting to large data growth and processing files quickly. It provides value through improved user experiences, faster development times, and lower costs. Case studies show how MongoDB helped companies by improving performance, simplifying development and management, reducing costs, and allowing easy scaling.

1. {Data: “12 Giugno 2014”, Ore: “14:00”
Location: “Datacenter Telecom Via settima strada 22, 35129 Padova”}

3. Problema: crescita di dati

4. Problema: crescita dei devices connessi

5. È una soluzione al problema della quantità di
informazioni: è un sistema che si adatta meglio
alla crescita consistente delle dimensioni degli
archivi, elaborandoli in poco tempo
Cos’è MongoDB ?

6. Valore di MongoDB
Strumento per
l’innovazione di nuove app
Migliore esperienza
utente
Time to market più
veloce
Riduzione del TCO

7. Ottimizzazione dei costi
Ottimizzazione in fase di sviluppo!
• Più facile da usare
• Sviluppo rapido
• Minori costi di mantenimento
• Nessun upfront di licenze
!
Hardware saving!
• Storage interno ( No SAN )
• Scale Out not Up
• Non sono richieste specifiche server
particolari
!
Dev. and Admin
Compute – Scale-Up Servers
Storage - SAN
Dev. and Admin
Compute – Scale-Up Servers
Storage - SAN

8. Agilità & Flessibilità!
• Evoluzione semplice del modello di dati
• Adattamento e cambi rapidi sulla struttura dati
Rappresentazione dati intuitiva e naturale!
• Sviluppatori sono più produttivi
• Le applicazioni risultano più semplici da gestire
Riduzione di operazioni di join e disk seek!
• La programmazione è più semplice
• Maggiori performance
Benefici del modello a documenti

9. Struttura più semplice

10. { !
_id: ‘Objectid(“4b2b9…”)’,!
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, … }!
]!
}!
MongoDB: Modello a Documenti
Database tradizionali: all’aumentare dei dati
diventano complessi e poco performanti
MongoDB: agile, organizzazione
dei dati facile ed intuitiva e molto performante.

11. Con MongoDB un modello di sviluppo più veloce

12. Alcuni casi studio

13. 43
Uses MongoDB to power enterprise social
networking platform
Case Study
Problem Why MongoDB Results
• Complex SQL queries,
highly normalized
schema not aligned with
new data types
• Poor performance
• Lack of horizontal
scalability
• Dynamic schemas
using JSON
• Ability to handle
complex data while
maintaining high
performance
• Social network analytics
with lightweight
MapReduce
• Flexibility to roll out new
social features quickly
• Sped up reads from 30
seconds to tens of
milliseconds
• Dramatically increased
write performance

14. 56
Serves variety of content and user services on
multiple platforms to 7M web and mobile users
Case Study
Problem Why MongoDB Results
• MySQL reached scale
ceiling – could not cope
with performance and
scalability demands
• Metadata management
too challenging with
relational model
• Hard to integrate
external data sources
• Unrivaled performance
• Simple scalability and
high availability
• Intuitive mapping
• Eliminated 6B+ rows of
attributes – instead
creates single document
per user / piece of content
• Supports 115,000+
queries per second
• Saved £2M+ over 3 yrs.
• “Lead time for new
implementations is cut
massively”
• MongoDB is default
choice for all new
projects

15. 53
Runs unified data store serving hundreds of
diverse web properties on MongoDB
Case Study
Problem Why MongoDB Results
• Hundreds of diverse
web properties built on
Java-based CMS
• Rich documents forced
into ill-suited model
• Adding new data types,
tables to RDBMS killed
read performance
• Flexible schema
• Rich querying and support
for secondary index
support
• Easy to manage
replication and scaling
• Developers can focus on
end-user features instead
of back-end storage
• Simplified day-to-day
operations
• Simple to add new brands,
content types, etc. to
platform

16. 47
Powers content-serving web platform on MongoDB
to deliver dynamic data to users
Case Study
Problem Why MongoDB Results
• Static web content
• Siloed data stores,
disparate technologies
• Unable to aggregate
and integrate data for
dynamic content
• Support for agile
development
• Easy to use and
maintain
• Low subscription and
HW costs
• Ability to serve dynamic
content
• Decreased TCO
• Replaced multiple
technologies with single
MongoDB database

17. 48
Stores user and location-based data in MongoDB
for social networking mobile app
Case Study
Problem Why MongoDB Results
• Relational architecture
could not scale
• Check-in data growth hit
single-node capacity
ceiling
• Significant work to build
custom sharding layer
• Auto-sharding to scale
high-traffic and fast-
growing application
• Geo-indexing for easy
querying of location-
based data
• Simple data model
• Focus engineering on
building mobile app vs.
back-end
• Scale efficiently with
limited resources
• Increased developer
productivity

18. 7,000,000+
MongoDB Downloads
150,000+
Online Education Registrants
25,000+
MongoDB User Group Members
25,000+
MongoDB Days Attendees
20,000+
MongoDB Management Service (MMS) Users

19. {Data: “12 Giugno 2014”, Ore: “14:00”
Location: “Datacenter Telecom Via settima strada 22, 35129 Padova”}
ISCRIVITI SUBITO