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VOLTDB AND FULL 360 PRESENT: HOW A FAST REAL-TIME
DATABASE HELPS A $2B LOYALTY PROGRAM LAUNCH
CAMPAIGNS IN DAYS RATHER THAN MONTHS
Rusty Ross, Solutions Architect, Full 360
Ryan Betts, CTO, VoltDB
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Collect Explore
AnalyzeAct
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Big Data analytic results:
1. Discoveries: seasonal predictions,
scientific results, long-term
capacity planning
1. Optimizations: market
segmentation, fraud heuristics,
optimal customer journey
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IN THE BIG CORNER
Systems facilitating exploration and analytics of large collections.
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Example Technologies
Columnar OLAP warehouses
Hadoop Ecosystem
• MapReduce
• Hive, Pig
• SQL.next: Impala, Drill, Shark
Example Applications
• User segmentation & pre-scoring
• Seasonal trending
• Recommendation matrices
• Building search indexes
• Data Science: statistical clustering,
machine learning
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IN THE FAST CORNER
Systems facilitating real time ingest, analytics and decisions against
incoming streams of events.
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Example Technologies
• Streaming frameworks
• Fast OLAP
• VoltDB (fast OLTP)
Example Applications
• Micro-personalization
• Recommendation serving
• Alerting/alarming
• Operational monitoring
• Data enrichment (ETL elimination)
• High throughput authorization
• Ex: API quota enforcement
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Problem #1
Sensors + Mobile + SaaS Infrastructures create streams of data that
overwhelm legacy databases.
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We make it simple, easy.
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Problem #2
Monetizing these data feeds requires writing real time per-event applications.
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We enable your ability to act
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Solution
VoltDB offers traditional OLTP database application support with the
performance to support real time applications against unlimited streams
of data.
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“Streaming data applications are really database applications if the database is fast enough.”Mike Stonebraker, Co-Founder, Advisor, VoltDB
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DATA ARCHITECTURE FOR FAST + BIG DATA
Enterprise Apps
ETL
CRM ERP Etc.
Data Lake
(HDFS, etc.)
BIG DATASQL on
Hadoop
Map
Reduce
Exploratory
Analytics
BI
Reporting
Fast Operational
Database
FAST DATA
ExportIngest /
Interactive
Real-time
Analytics
Fast Serve
Analytics
Decisioning
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