SlideShare a Scribd company logo
Sergey Boldyrev
November 2011
ARTEMIS
M3, a prototype of
Data management
platform
1 © 2010 Nokia
Problem statement
As we scale, the cost curve is driven by:
- Growth of data per user
- Complexity to scale and sharing data across silos
- Non-linear data layer scaling
- Less efficient resource utilization
- Globalization – data traffic & legal restrictions
Issues:
1. Vertical scalability
2. Underutilization
3. Too many integrations
4. Duplicated data
5. Duplicated development effort
6. Ineffective and lengthy deployment model
Paradigm Shift needed, the M3
Enterprise data model
Data on the phone
Data only
Silos of data
Fragmented data views
Architectural diversity
Scalability barriers
Generic data
Cloud data model
Data in the cloud
Knowledge and visibility
Integrated and shared data
Cross services unified data views
Uniformed data architecture
Near linear scalability
Personal, Contextual, Relevant
M3
Old World DataOS
DataOS
The Data OS is a key component in addressing listed issues, providing
• a performant,
• scalable,
• low-cost
platform for shared data and analytics
DataOS has adopted core M3 principles
1. Decouple data from applications
- Users own their own data
- Data is shared between all applications
- Generic data collection are done independently of applications that consume the
data
- Enabled generic operations on data to allow infrastructure to participate in data
integration, distribution and other tasks
2. All data is universally addressable
- Driven by integration demands implied by #1
3. Divide into fast and slow world and conquer
- Separate real-time transactions from slower back-ends
M3 Architecture Foundation in DataOS
- Distributed Data Management
- High availability
- High performance, low latency
- Incremental scalability
- Eventual consistency
- Self Managing : rebalancing, self healing
- Data grid, bring algorithm to data
- Robust data recovery
- Low total cost of ownership
- Minimal administration, full automation
Reference
1. M3 (smart M3) project
2. Ovi
3. Distributed data management platform

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Data management platform

  • 1. Sergey Boldyrev November 2011 ARTEMIS M3, a prototype of Data management platform 1 © 2010 Nokia
  • 2. Problem statement As we scale, the cost curve is driven by: - Growth of data per user - Complexity to scale and sharing data across silos - Non-linear data layer scaling - Less efficient resource utilization - Globalization – data traffic & legal restrictions Issues: 1. Vertical scalability 2. Underutilization 3. Too many integrations 4. Duplicated data 5. Duplicated development effort 6. Ineffective and lengthy deployment model
  • 3. Paradigm Shift needed, the M3 Enterprise data model Data on the phone Data only Silos of data Fragmented data views Architectural diversity Scalability barriers Generic data Cloud data model Data in the cloud Knowledge and visibility Integrated and shared data Cross services unified data views Uniformed data architecture Near linear scalability Personal, Contextual, Relevant M3 Old World DataOS
  • 4. DataOS The Data OS is a key component in addressing listed issues, providing • a performant, • scalable, • low-cost platform for shared data and analytics
  • 5. DataOS has adopted core M3 principles 1. Decouple data from applications - Users own their own data - Data is shared between all applications - Generic data collection are done independently of applications that consume the data - Enabled generic operations on data to allow infrastructure to participate in data integration, distribution and other tasks 2. All data is universally addressable - Driven by integration demands implied by #1 3. Divide into fast and slow world and conquer - Separate real-time transactions from slower back-ends
  • 6. M3 Architecture Foundation in DataOS - Distributed Data Management - High availability - High performance, low latency - Incremental scalability - Eventual consistency - Self Managing : rebalancing, self healing - Data grid, bring algorithm to data - Robust data recovery - Low total cost of ownership - Minimal administration, full automation
  • 7. Reference 1. M3 (smart M3) project 2. Ovi 3. Distributed data management platform