Inge Os Sales Consulting Manager Oracle Norway

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1 Inge Os Sales Consulting Manager Oracle Norway

2 Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database Machine Oracle & Sun

3 Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database Machine Oracle & Sun

4 Oracle Fusion Middelware, strategy

5 Oracle Fusion Middelware, strategy

6 Oracle Fusion Middelware, strategy

7 From business prosess to implementation

8 Oracle Application Integration Architecture

9 Security as a service

10 Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database Machine Oracle & Sun

11 Oracle Database 11g Release 2 Specific Areas of Cost Reduction Reduce hardware capital costs by factor of 5x Reduce storage costs by factor of 20x Improve performance by at least 10x Eliminate downtime AND unused redundancy Raise DBA productivity by at least 2x Considerably simplify your software portfolio Reduce upgrade costs by a factor of 4x

12 Consolidate onto the Grid Oracle s Grid Computing Architecture In-Memory Database Cache Real Application Clusters Enterprise Manager Automatic Storage Management

13 Oracle Database 11g Release 2 Dynamic Cluster Partitioning via Server Pools Front Office App Servers DW Back Office Free RAC One Server Pools Dynamically assigns the server resources required to run specific workloads Both Application and Database Pools Policy Managed Min and Max Servers Relative Importance Unassigned Servers go to Free Pool

14 Manage Data Growth Partition for performance, management and cost ORDERS TABLE (7 years) % Less Active 5% Active Low End Storage Tier 2-3x less per terabyte High End Storage Tier

15 Significantly Reduce Storage Costs Advanced OLTP Compression Compress large application tables Transaction processing, data warehousing Compress all data types Structured and unstructured data types Improve query performance Cascade storage savings throughout data center Up To 4X Compression

16 Improve performance by at least 10x Oracle Database 11g Release 2 Newer Nehalem Chipsets are very fast Currently only available in commodity class machines Only RAC enable customers to uptake them In Memory Database Cache offloads processing to be offloaded to the middle tier machines, removes latency 10x performance improvement Oracle Exadata and Oracle Database Machine improve Data Warehousing performance by at least 10X

17 Edition-based redefinition Oracle Database 11g Release 2 brings the edition, the editioning view, and the crossedition trigger Code changes are installed in the privacy of a new edition Data changes are made safely by writing only to new columns or new tables not seen by the old edition An editioning view exposes a different projection of a table into each edition to allow each to see just its own columns A crossedition trigger propagates data changes made by the old edition into the new edition s columns, or (in hot-rollover) vice-versa

18 Real Application Testing Workload for 1,000s of Online Users Replayed Capture Replay Workload PRODUCTION TEST

19 Managing Complexity Automated Self-management Automated: Storage Memory Statistics SQL tuning Backup and Recovery Advisory: Indexing Partitioning Compression Availability Data Recovery

20 Sun Oracle Database Machine Optimized for strategic warehousing Ad hoc queries over detail data Only Oracle provides 21 GB/sec per rack of IO bandwidth, with up to 50 GB/sec with Flash Optimized for operational warehousing Tactical, short-running queries integrated with operational processes Only Oracle provides advanced warehouse indexing capabilities running at 1M IOPS Optimized for real-world data loading Only Oracle provides multi-version read consistency with the ability to load at 5TB/hr Optimized for advanced analytics Only Oracle provides integrated OLAP, data mining, spatial and statistics

21 Sun Oracle Database Machine Product Family Basic Quarter Rack Half Rack Full Rack 2-8 Full Racks Database Servers Exadata Storage Servers Total Disk Capacity 7.2 TB 21 TB 50 TB 100 TB TB User Data (uncompressed) 2 TB 6 TB 14 TB 28 TB TB I/O Throughput (disks) 1.5 GB/sec 4.5 GB/sec 10.5 GB/sec 21 GB/sec GB/sec I/O Throughput (flash) 3.6 GB/sec 11 GB/sec 25 GB/sec 50 GB/sec GB/sec I/O per Second (IOPS) 75, , ,000 1,000,000 1M 8M Racks N/A

22 Scale-Out Architecture Business Data Protection ASM Reliable Storage Pool Exadata Database Intelligent Storage The database, ASM, and Exadata Cells each play a role in Oracle s scale-out storage architecture Responsibilities are placed in the optimal location DB Business Data Protection ASM Reliable Storage Pool Exadata Cell Database Intelligent Storage Seamless integration simplifies management

23 World's First OLTP Database Machine with Sun FlashFire Technology RAC Cluster DB server on standard Linux HW Infiniband for interconnect and storage Exadata storage cells Standard Linux based controller Flash Drives SATA or SAS disks

24 Smart Scans Exadata cells implement smart scans to greatly reduce the data that needs to be processed by database Only return relevant rows and columns to database Offload predicate evaluation Data reduction is usually very large Column and row reduction often decrease data to be returned to the database by 10x

25 Simple Query Example Exadata Storage Grid What were my sales yesterday Oracle Database Grid Select sum(sales) where Date= 24- Sept Retrieve sales amounts from Sept 24 SUM

26 Exadata is Smart Storage Compute Intensive Processing Bandwidth Intensive Searches Database Server Compute and memory intensive data processing executes in database servers Fully-parallelized joins and aggregations Exadata Storage Server IO-bandwidth intensive searches executes in storage servers Exadata Smart Scans and Exadata Storage Indexes filter out data that is not relevant to a query Database Servers and Exadata storage work in conjunction to execute SQL Exadata cell is smart storage, not a complete database node

27 New Exadata Database Processing in Storage Exadata storage servers implement data intensive processing in storage Row filtering based on where predicate Column filtering Join filtering Incremental backup filtering Scans on Hybrid Columnar Compressed data Scans on encrypted data Data Mining model scoring 10x reduction in data sent to DB servers is common No application changes needed Processing is automatic and transparent Even if cell or disk fails during a query

28 Exadata Storage Index Transparent I/O Elimination with No Overhead New Exadata Storage Indexes maintains summary information about table data in memory Stores MIN and MAX values of filter columns Typically one index entry for every MB of disk Eliminates disk I/Os if MIN and MAX can never match where clause of a query Negative index Completely automatic and transparent Order_date Ship_date Cust _ID Prod _ID Amount 03-SEP SEP , SEP SEP , SEP OCT , SEP OCT , SEP OCT , MIN ship_date = 19-SEP-2009 MAX ship_date = 07-OCT-2009 MIN ship_date = 01-OCT-2009 MAX ship_date = 03-NOV SEP NOV , Select * from orders where ship_date < 31-SEP-2009 Only first set of rows can match

29 Sun Oracle Database Machine: Optimized for large scans 10 TB of user data Requires 10 TB of IO 1 TB with compression 100 GB with partition pruning Subsecond On Database Machine 20 GB with Storage Indexes 5 GB with Smart Scans 2000X less data needs to be processed

30 Exadata Flash Extreme Performance New Sun Oracle Database Machine has 5 TB of flash storage 4 high-performance flash cards in every Exadata Storage Server Oracle is the First Flash Optimized Database Smart Flash Cache caches hot data Not just simple LRU Knows when to avoid caching to avoid flushing cache Allows optimization by application table

31 Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database Machine Oracle & Sun

32

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