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StreamInsight 01 – Introducing SQL Server 2008 R2 StreamInsight. SQL10R2UPD05-DECK-01 [Presenter Name] [Presenter Title] [Company Name]. Module Overview. Introducing StreamInsight Querying Events in StreamInsight Designing StreamInsight Event Models and Adapters

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streaminsight 01 introducing sql server 2008 r2 streaminsight

StreamInsight01 – Introducing SQL Server 2008 R2 StreamInsight


[Presenter Name][Presenter Title] [Company Name]

module overview
Module Overview
  • Introducing StreamInsight
  • Querying Events in StreamInsight
  • Designing StreamInsight Event Models and Adapters
  • Installing, Deploying, and Maintaining the StreamInsight Runtime Engine
  • Complex Event Processing
  • Introducing StreamInsight and the Overall Architecture
  • Demo: End-to-End Solution
complex event processing
Complex Event Processing
  • Processing and querying of event data streams
  • Data queried while “in flight”
  • May involve multiple concurrent event sources
  • Works with high data rates
  • Aims for near-zero latency
isn t this just a database application
Isn’t This Just a Database Application?



output stream

input stream


goals of complex event processing
Goals of Complex Event Processing
  • Identify from seemingly unrelated events:
    • Patterns
    • Relationships
    • Gaps (expected events that did not occur)
    • Abstractions
  • Trigger immediate response actions
sweet spot for complex event processing
“Sweet Spot” for Complex Event Processing

Relational Database Applications

CEP Target Scenarios

Operational Analytics Applications (e.g., Logistics)

Data Warehousing Applications

Web Analytics Applications

Manufacturing Applications

Financial Trading Applications

Monitoring Applications

Aggregate Data Rate (Events/sec)

usage example capital markets
Usage Example: Capital Markets
  • Algorithmic trading
  • Smart order routing
  • Real-time profit and loss
  • Rapid analysis of transactional cost
  • Fraud detection
  • Risk management
usage example click stream analysis
Usage Example: Click-Stream Analysis
  • Often 100,000 events per second
  • Automate
    • Page layout
    • Navigation
    • Presentation
    • Targeted advertising
usage example communications
Usage Example: Communications
  • Real-time network monitoring
  • Quality of service monitoring
  • Location-based services
  • Fraud detection
  • Intrusion detection
usage example command intelligence
Usage Example: Command Intelligence
  • Battlefield control
  • Monitoring of resource locations
  • Intrusion detection
  • Network traffic analysis
    • Emails
    • Network traffic
    • Watch lists
    • Financial movements
usage example manufacturing
Usage Example: Manufacturing
  • Asset monitoring
  • Aggregation of machine-based sensor data
  • Generation of alerts in error conditions
  • Identifying the “golden batch”
usage example casino monitoring
Usage Example: Casino Monitoring
  • Gaming machine event analysis
  • Card table analysis
    • Fraud detection
    • Profit and loss in real-time
  • Targeted advertising
    • Player behavior
    • Loyalty system implementation
usage example mpg and virtual worlds
Usage Example: MPG and Virtual Worlds
  • Real-time monitoring
  • Managing player interest
  • Website traffic analysis
  • Detecting and eliminating undesired behaviors
  • Understanding behavioral patterns
usage example public health
Usage Example: Public Health
  • Patient management
  • Outbreak management
  • Trend detection
  • Insurance risk analysis
usage example logistics
Usage Example: Logistics
  • Vehicle management
  • Supply chain forecasting and tracking
  • Maritime logistics
  • GPS tracking
usage example energy management
Usage Example: Energy Management
  • Monitoring
    • Consumption
    • Variations
  • Detecting outages
  • Smart grid management
  • Aggregating data across the grid
competitive landscape
Competitive Landscape

Industry Forum:

  • Complex Event Processing
  • Introducing StreamInsight and the Overall Architecture
  • Demo: End-to-End Solution
microsoft streaminsight
Microsoft StreamInsight
  • Platform for development and deployment of CEP applications
  • High-throughput stream processing architecture
  • .NET-based development environment
streaminsight purposes
StreamInsight Purposes
  • Monitor data from multiple sources and detect:
    • Meaningful patterns
    • Trends
    • Exceptions
    • Opportunities
  • Analyze data without storing it first
  • Provide low-latency processing
  • Trigger response actions
  • Mine events for new business KPIs
benefit net development environment
Benefit: .NET Development Environment
  • Use .NET languages such as C#
  • Query using LINQ
  • Take advantage of developer familiarity with .NET
  • Reduce development times (and costs)
  • Extend StreamInsight with .NET code
benefit performance and data throughput
Benefit: Performance and Data Throughput
  • Highly parallel execution platform
  • In-memory caches
  • Incremental result computation
  • All processing triggered by incoming events
    • Avoids polling overhead
  • Can handle out-of-order events
  • Can incorporate static reference or historical data
benefit deployment and management
Benefit: Deployment and Management
  • Multiple deployment scenarios
    • Fully integrated via embedded DLL
    • Standalone server (multiple apps and users)
  • Built-in monitoring and management
    • Management interface
    • Diagnostic views
    • Manageability framework allows for remote monitoring
    • Standalone event flow debugger
streaminsight event data flow
StreamInsight Event Data Flow

Data Sources, Operations, Assets, Feeds, Sensors, Devices

Input Data Streams

OutputData Streams

Input Data Streams

CEP Engine


& Record


& Design











Operational Data Store & Archive

CEP Engine





end to end solution

End-to-End Solution



demo scenario highway monitor
Demo Scenario: Highway Monitor
  • Major highway
  • 8 lanes
  • 2 directions
  • 6 toll points
  • Vehicle types
    • Car
    • Bus
    • Truck
    • Ambulance
    • Taxi
toll point timings
Toll-Point Timings
  • Vehicles measured multiple times
  • Electronic tag captured
  • Speed measured
  • Vehicle type determined
toll point measurements
Toll-Point Measurements
  • EventID – guid
  • TollPointId – which toll point: 0 to 5
  • DirectionId – which direction: 0 (North) or 1 (South)
  • Lane – which lane: 0 to 7
  • VehicleTypeId – enumeration: 0-car, 1-bus, 2-truck, 3-taxi, 4-ambulance
  • TagId – vehicle’s individual tag
  • EnterGate – datetime when vehicle entered gate
  • MillisecondsToPassSpeedCheckPoint – how long vehicle took to travel 10m
  • ExitGate – datetime when vehicle exited gate
  • StreamInsight Website
  • StreamInsight Books Online
  • StreamInsight Forums
  • StreamInsight Whitepaper
    • 20Overview.docx

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