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Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
Opensourceday 2014-iot
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Opensourceday 2014-iot

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  • 1. Technical Evangelist,MongoDB
 @tgrall Tugdual “Tug” Grall @mongodb The Internet of Things Managing the Database Complexity
  • 2. @tgralltug@mongodb.com Once upon a time
  • 3. @tgralltug@mongodb.com Today
  • 4. @tgralltug@mongodb.com The IoT is already here ! World
 Population Connected Devices Connected Devices per Person 6.3 Billion 500 Million 0.08 2003 6.8 Billion 12.5 Billion 1.84 2010 7.2 Billion 25 Billion 3.47 2015 7.6 Billion 50 Billion 6.58 2020 More connected devices than people Source: Cisco
  • 5. @tgralltug@mongodb.com Lots of sensors -> Lots of data
  • 6. @tgralltug@mongodb.com High-Speed Ingestion
  • 7. @tgralltug@mongodb.com High-Speed Ingestion
  • 8. @tgralltug@mongodb.com High-Speed Ingestion
  • 9. @tgralltug@mongodb.com Data Growth 50-fold growth from the beginning of 2010 to the end of 2020 40,000 Exabytes
 
 = 40,000,000,000,000 Gigabytes ! = 5,200 Gigabytes for every man, woman and child in 2020
  • 10. @tgralltug@mongodb.com Before you can process Big Data You must store it
  • 11. MongoDB
  • 12. @tgralltug@mongodb.com MongoDB Vision To provide the best database for how we build and run apps today Build • New and complex data • Flexible • New languages • Faster development Run • Big Data scalability • Real-time • Commodity hardware • Cloud
  • 13. @tgralltug@mongodb.com 7,000,000+ 
 MongoDB Downloads 150,000+ 
 Online Education Registrants 35,000+
 MongoDB Management Service (MMS) Users
 30,000+ 
 MongoDB User Group Members 20,000+ 
 MongoDB Days Attendees Global Community
  • 14. @tgralltug@mongodb.com Document Data Model { vehicle_id: ‘123abc’, vehicle_driver: ‘Miller’, base: ‘London’, tracking: [ { timestamp: ‘2014-01-17-12:00:00’, location: [51.123,-0.232], speed: 55, … }, { timestamp: ‘2014-01-17-12:15:00’, location: [51.224,-0.238], speed: 5, … } } } Perfect fit for M2M apps • Rich,multi-structured data • Rapidly changing data Agility and flexibility • Dynamic schema evolves • Easy to ingest new data Intuitive data structure • Developers are more productive • Less code
  • 15. @tgralltug@mongodb.com Many devices, Many formats
  • 16. @tgralltug@mongodb.com Horizontal Scalability: Sharding Shard 1 Shard 2 Shard nShard 3 … Horizontally Scalable
  • 17. @tgralltug@mongodb.com High Availability : Replication
  • 18. Use Cases
  • 19. @tgralltug@mongodb.com Bosch Internet of Things Platform
  • 20. Questions? Stop by our booth to learn more about MongoDB
  • 21. @tgrall opensourceday ThankYou

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