1. ICONICS 2008 Worldwide Customer Summit Boston, MA Dave Oravetz, US Habib Rehman, Australia Carl Harper, UK Andre Scherpenzeel, UK

2. To provide not just a ‘data logger’, but a ‘data historian’ Provide easy integration of data historian with other applications Provide competitive historian for large projects Compete with the specialist products ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 2

3. High Performance  Large tag quantities at high rates Small ‘data value’ footprint  Efficient long duration storage 64 bit &.NET Technology  Extendable platform allowing for future growth ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 3

4. Easier data access/interaction  OPC UA for ICONICS products  API for custom applications  SQL interface  Integrate into database systems  Query from any OLE-DB client ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 4

5. ICONICS - Hyper Historian Competition  GE – Proficy  Rockwell – Factory Talk  OSI – Echo Data Historian  AspenTech – Info Plus  Wonderware – Historian 9  Simatic – IT Historian ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 5

6. ICONICS 2008 Worldwide Customer Summit – Boston, MA 6 ICONICS Hyper Historian Standard Edition ICONICS Hyper Historian Enterprise Edition Web Configuration Web Viewers (Native WPF) 3D Charting Archive Compression SQL Query Interface Persistence OPC-UA (Native) Data Collection Acceleration (OPC In-proc option)  Remote Collectors Redundancy Store & Forward Multi-CPU

7. Hyper Historian Provides  Equal or better throughput performance  Equal or better maximum tag counts  Extensive client connectivity features  OPC UA, OPC HDA, OLE-DB, Excel, SQL Server, native API, ICONICS Native  Extensive use of recent technologies  Vista 64/2008 Server 64/.NET ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 7

8. Hyper Historian Provides  Extensive client connectivity features  OPC UA, OPC HDA, OLE-DB, Excel, SQL Server, native API, ICONICS Native  Extensive use of recent technologies  Vista 64/2008 Server 64/.NET ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 8

9. Comparison ICONICS 2008 Worldwide Customer Summit – Boston, MA, April, 2008 9

10. 10 Hyper-Historian Key Benefits Efficient  High Performance  High Compression Reliable  Redundancy  Store and Forward Data Accessibility  TrendWorX64 Viewer  SQL Query Interface Data Editing Easy to Configure  Remote Configure-ability  Web-based  Online Flexible, Automated Archiving Scalable  Flexible Architecture

11. Architecture and Configuration

12. 12 Hyper-Historian Architecture Hyper-Historian Components  Data Collector  Data Logger  Workbench Configuration  3D Chart Control  SQL Query Interface

13. Real-time Data Logger Remote Data Collectors ICONICS Workbench System Configuration & Administration Operator Controls BizViz SolutionsThird Party Solutions OPC DA OPC UA OPC XML DA Standard SQL Query RAMDisk SQL 2005 SQL 2008 Historical Data Storage On Event SNMP BACnet Databases Real-time Data OPC-UA Configuration Database Store & Forward Reports Productivity Analytics Enterprise Bridging Custom Portals Mobile & Wireless Custom Applications Configuration Archive Management TrendWorX 2D & 3D Charts Manually Entered Data Operator Comments Remote Data Collectors Store & Forward... Auto Archiving External Storage

14. 14 Hyper-Historian Collector Collects Data From:  OPC DA Servers  OPC XML DA Servers  OPC UA Servers  GenBroker Plugins  SNMP  BACnet  Databases Portable  XP 64-Bit  Vista 64-Bit  Server 2003 64-bit  Server 2008 64-bit

15. 15 Hyper-Historian Collector Local or Remote Deadband Filtering Advanced Filtering  Maximum  Minimum  Average  Standard Deviation  Totalizer  Running Maximum  Running Minimum  Running Average  Moving Maximum  Moving Minimum  Moving Average  Most Recent On Time Redundant Collectors Store and Forward

16. 16 Hyper-Historian Logger Logging Options  High Performance Disk Based  RAM Memory-Based Persistent Data  Raw  Advanced Filtered  Aggregate s Data Types  Boolean  Integer  Float  String Filtering  None  Deadband  Swinging D oor

17. 17 Hyper-Historian Logger Conditional Logging  UDM Trigger Based Memory Persistent Logging  Configurable Logging Period  Option to Log to Disk upon Event  Configurable Pre and Post Event Store Aggregate Logging  Summary Tags for High-speed playback of Summary Portable  XP X64  Vista X64  Server 2003 X64  Server 2008 X64 Redundant Loggers

18. 18 Hyper-Historian Configuration Online Configuration Web Based Configuration Based on Web Workbench Toolkit  Consistent Look-and-Feel to TrendWorX64 Configurator

19. Configuration Demo

20. Performance and Runtime

21. 21 Hyper-Historian Performance 50,000+ Values Logged per Second 150,000+ Tags Collection Resolution to 10 MS Immediate playback of Logged data  No wait for Database writes

22. GENESIS Historian Benchmarks AMD Athlon 64 X2 Dual Core, 2.86 GHz 8 GB Memory Windows Vista64 Business SP1 Twx32Twx64Hyper Historian 1,000 Tags @ 1 s4% (34)5%1.8% 10,000 Tags @ 1 s34.5%42%22% 25,000 Tags @ 1 sn.a49%46% 50,000 Tags @ 1 sn.a.n.a68%

23. GENESIS Historian Benchmarks AMD Athlon 64 X2 Dual Core, 2.86 GHz 8 GB Memory Windows Vista64 Business SP1 Twx32Twx64Hyper Historian 1,000 Tags @ 1 s217 MB140 MB133 MB 10,000 Tags @ 1 s690 MB1460 MB857 MB 25,000 Tags @ 1 sn.a.7300 MB1480 MB 50,000 Tags @ 1 sn.a.n.a2630 MB

24. Performance Hyper Historian Sample Benchmark Results TagsRateCPU Load 10,000200 ms29% 25,000500 ms56% 50,0001 s60% 100,00010 s8% 150,00010 s10%

25. 25 Data Compression Deadband Filter Swinging Door Algorithm “Advanced” Filtering Small Data “Footprint” Low overhead Binary file store Aggregate Tags

26. Swinging Door Efficiency Aggressive Deadband filter: 12% (12 values) 102 Raw Values (per cycle) Deadband filter: 31% (32 values) Swinging Door filter: 12% (12 values)

27. Deadband Filter Limitations 1 3 6 8 21 13 19 14 17 20 15 18 11 12 2 4 5 7 9 10 16 Deadband Filter Swinging Door ► Stores unneeded samples (6, 7, 15, 16) ► Misses inflection samples (4, 13) ► Higher Compression ► Better accuracy

28. Data Footprint TrendWorX32 / TrendWorX64  ~28 Bytes / 32-bit Float  100 Tags @ 1s for 1 day  ~300 Mbytes Hyper Historian  ~7 Bytes / 32-bit Float  100 Tags @ 1s for 1 day  ~70 Mbytes

29. 29 Hyper-Historian File Archiving Advanced file maintenance and Archiving  Control of Disk Space Use  Backup of Data  Easy Re-attachment of Backup Archiving Based on  UDM Trigger  File Size  Age of Data

30. Compression Demo

31. Clients

32. 32 Hyper Historian Clients TrendWorX64 Chart Control SQL Query Interface ReportWorX BridgeWorX Productivity Analytics Third Party

33. 3D Charting Capabilities  Real-time And Historical Trend Data Rotate to Change Perspective Out-of-the-box Chart Categories Plug-in New Chart Types Combine Charts for Analysis 33

34. Summary View Paging (Fwd & Back) Zoom 34

35. 35 Hyper-Historian SQL Query Look and Feel of SQL Server Various Output formats Select, Insert, Update, Delete Support

36. 36 Hyper-Historian SQL Query Advanced Data Query Support  Time-in-State  Best Fit  Time-Weighted Average  Integral  Slope  Counter

37. 37 Hyper-Historian Data Editing API to Edit Logged Data  Edited data is Marked  Original data is kept HDA Playback Options  Original data only  Original data with edited data  Combination – showing both GUI for Manual Edits API for bulk edits

38. 38 Other Hyper-Historian Features Integrated into MonitorWorX TraceWorX Support GenEvents Support

39. Client Demo

40. 40 Hyper-Historian Key Benefits Efficient  High Performance  High Compression Reliable  Redundancy  Store and Forward Data Accessibility  TrendWorX64 Viewer  SQL Query Interface Data Editing Easy to Configure  Remote Configure-ability  Web-based  Online Flexible, Automated Archiving Scalable  Flexible Architecture

41. 41 Hyper-Historian Questions ?

42. TrendWorX64 vs. Hyper-Historian TrendWorX64 LoggerHyper-Historian Logger Based on TrendWorX32 DesignNew Design – From Ground Up SQL, Oracle, or MySQL databaseProprietary Database 25,000+ values / second50,000+ Values / Second 50,000+ Tags150,000+ Tags Deadband FilterDeadband & Swinging Door Filters ~28 Bytes / Logged 32-bit Float~7 Bytes / Logged 32-bit Float Centralized LoggerDistributed Architecture Limited SQL Query SupportStrong SQL Query Support …Conditional Logging …Event-Based Logging …Data Editing / Data Insert …Aggregate Value Logging Non RedundantRedundancy / Store and Forward

43. 43 Future Goals – V10.5 HDA Server / GENESIS32 Integration 32-bit Collector Standalone Installation for Collector Redundancy & Store and Forward Data Insert Grid Data Insert Utility Swinging Door at Collector Optimizations (>100,000 values/sec) MS Cluster Aware

44. 44 Future Goals – Part II Twx32 Configuration Import SQL Query Interface Extensions  Quality Filter SQL Server Logger Dynamic Calculations Ability to monitor health via SNMP Data Collection from more sources  OPC AE Support for more tags (>500,000)