Date post: | 22-Jan-2017 |
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Software |
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REAL-T IME ANALYTIC S USING SPARK AND
OBJECT IV ITY ’S THINGSPAN
BY O B J E C T I V I T Y I N C .
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OBJECTIV ITY ’S PEDIGREE• Headquartered in Silicon Valley since 1988
• Pioneer in high-performance distributed object data technology
• Decades of experience in “beyond petabyte” data volumes
• Deep domain expertise in massively scalable graph analytics
• Software validated and proven by Global 1000 customers and partners
WHY GRAPH?• Use actual relationships in
addition to statistical correlation
• Ultra-fast navigation and path finding without joins
• Combine conventional and graph analytics to support advanced pattern finding
• In-Memory graph limited by RAM and machine
• Billions of nodes and edges require parallelism and a distributed graph
SCALING GRAPHS
F INANCIAL USE CASES
• Smart Trading (alpha generation, portfolio optimization)
• Regulation and Compliance (Know Your Customer)• Cybercrime Prevention and Detection (security
breaches)
• Uses: Alpha generation; portfolio optimization
• Data sources: Financial accounts, markets, sectors, exchanges, reference data, social media
• Opportunities: • Compare streaming data to
historical trends • Determine relationships
between transactions to forecast stock value
SMART TRADING
• Uses: Know Your Customer; detect insider trading and securities fraud
• Data sources: Financial accounts, emails, SMS, social media
• Opportunities: • Accurately understand risk• Prevent loss of revenue due
to rogue activities and fines
R E G U L AT I O N & C O M P L I A N C E
• Uses: Identify unusual patterns indicative of security breaches
• Data sources: Network logs (firewall, proxy, VPN, DNS), emails, HR data
• Opportunities: • Correlate data from security
and network solutions with internal and semantic web apps
• Be proactive, not reactive
C Y B E R C R I M E P R E V E N T I O N
• ThingSpan is an massively scalable distributed platform purpose-built for real-time graph analytics and relationship discovery
• ThingSpan is architected to integrate and leverage major open source technologies – HDFS, YARN, Spark, Kafka
• ThingSpan supports a mixed workload environment with high-speed ingest and parallel querying
P O S I T I O N I N G
A N A LY T I CS
A FT E R-T H E - FACTS T R E A M I N G
P L AT F O R M
I N -T I M E
Time to Production
Time to Insight
T I M E -T O - I N S I G H T C O N T I N U U M
Real-time insight as events happen• ThingSpan + Spark Streaming
In-time context involving streams and state• ThingSpan + Graph Exploration
After the fact insight involving context and state• ThingSpan + Spark
Pattern Finding• Long-term insights
T H I N G S PA N A R C H I T E C T U R E
THINGSPAN STACK
D I S T R I B U T E D P R O C E S S I N G & D A T A B A S E
Hadoop Distributed File System
Distributed from top to bottom
T H A N K S F O R R E V I E W I N G !
Objectivity’s ThingSpan
• Real-time graph analytics
• Apache Spark-enabled
• Hadoop (HDFS)-ready
CONTACT US:
Headquartered in San Jose, CA
Contact Us: 408-992-7100
http://www.objectivity.com