Enterprise Applications Product Family Contracts Corporate Performance

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Enterprise Applications Product Family – Contracts, Corporate Performance Management, Customer Relationship Management, Financials, Human Resources, Interaction Center, Intelligence, Maintenance Management, manufacturing, Marketing, Order Management, Procurement, Product Lifecycle Management, projects, Sales, Service, Supply Chain Planning, Supply Chain Management Oracle Ebusiness Suite online document available

Infrastructure Software

A Brief look at Oracle’s Database History Oracle 7 – Oracle Parallel Server Oracle 8 i – Transition to Real Application Clusters begins Oracle 9 i – – Integrated Data Warehousing Real Application Clusters Oracle 10 g – New grid capable features

Federated Database A logical unification of distinct databases Independent servers No shared resources (including disk) Connected by LAN

Shared Disk Architecture Equal access to all disks No notion of data ownership on any node Managed by Oracle’s Real Application Clusters (RAC)

Shared Disk Architecture: Scalable Nodes can be dynamically added and removed from the grid Adding and removing nodes does not require data to be redistributed Multi-version read consistency model Based upon Real Application Clusters

Multi-Version Read Consistency Writers never block readers and readers never block writers Data is tracked by a System Change Number (SCN) Always provides consistent and accurate results Non-escalating row-level locking – Locks are contained at the row level

Example: System Change Number

Shared Disk Architecture: Availability The loss of a cluster node does not cause a loss of data The loss of a cluster node does not cause another node to “take over” data Processes can be redistributed to other nodes

Traditional Shared-Disk Clustered Databases Maintaining data coherency is a hard problem – – Need to synchronize updates to shared data The disk is the only medium for data sharing Disk I/O latencies appear in the critical path when multiple nodes access shared data Disk-based coherency is the main bottleneck to achieving a scalable shared disk cluster – Only synthetic fully partitioned workloads scale!

Oracle Real Application Clusters (RAC) Ÿ An application transparent clustered database – single node applications run and scale with no changes Ÿ Cluster interconnect fabric replaces the disk as the medium for inter-node data sharing Ÿ Cache Fusion protocol for data sharing results in a scalable cluster for OLTP and DSS workloads

Oracle RAC Architecture Centralized Management Console Application Servers/ Network Low Latency Interconnect High Speed Switch or Interconnect Clustered Database Instances Hub or Switch Fabric Mirrored Disk Subsystem Users No Single Point Of Failure Shared Cache Storage Area Network Drive and Exploit Industry Advances in Clustering

What is Cache Fusion? Ÿ The underlying technology that enables RAC Ÿ Protocol that allows instances to combine their data caches into a shared global cache – Global Cache Service (GCS) coordinates sharing Ÿ Key features are – – – Direct sharing of volatile buffer caches Efficient inter-node messaging framework Fast recovery from node failures using cache and CPU resources from all surviving nodes

Data Sharing Problem Ÿ Read Sharing for Queries – query needs to read a data block that is currently in another instance’s buffer cache. Ÿ Write Sharing for Updates – update needs to modify a data block that is currently in another instance’s buffer cache. Ÿ With Cache Fusion, a disk read is performed only if the block is not already in the global shared cache

Cache Fusion Read Sharing Ÿ Uses Oracle’s Consistent Read (CR) scheme – – undo is applied to make a block transactionally consistent to a System Change Number (SCN). a CR copy is shipped to the requesting instance 1 225 Data Block Query SCN 200 2 3 200 Instance A CR Copy Instance B

Cache Fusion Write Sharing Ÿ Multiple dirty copies of a data block can exist in the global cache, but only one is current Ÿ The current copy can move between instances without first being written to disk – Changes are logged if not already on disk Ÿ Non-current dirty copies can directly service queries from any node and instance recovery

Cache Fusion Write Sharing Instance A Instance B 4 Current 225 Update Block 10 1 Master 2 3 Copy 225 Requester GCS 200 Instance C Holder

Efficient Inter-Node Messaging Ÿ Messaging cost independent of cluster size – At most 3 nodes involved in a request Ÿ requester, holder and master (directory) Ÿ number of messages to service a request is bounded Ÿ Inter-Node Message Latency – exploits high performance interconnect substrates so that on-the-wire message transmission times are minimal Ÿ Frequency of Inter-Node Synchronization – – adaptive directory migration based on access patterns fast reconfiguration of resources when a node joins/leaves

Oracle Grid Computing Goals Storage Grid Database Grid Half the Cost Highest Quality of Service Easiest to Manage Application Grid Control

Problem with Today’s IT Infrastructure Islands of Computing Resource – – Some are melting down Some are almost idle CRM High Costs – – – Hardware Labor Software ERP Hard to Align with Business Priorities DW

Solution: Computing On Demand Mainframe Model Partitioning of one large server Built with high quality, high cost parts Complete, integrated software High quality of service at high cost Grid Computing Model Coordinated use of many small servers Built with low cost, standard, modular parts Open, Complete, integrated software High quality of service at low cost

Early Grid Computing Desktop Grids – SETI@home Scientific Research Grids – Globus Toolkit, CERN What about Grids for the Enterprise? 11

Requirements for Enterprise Grids Run all your applications Stores all your information Highly scalable, available, reliable Secure Easy to manage – – Make individual systems self-managing Manage thousands of servers at once

Introducing Oracle 10 G Ÿ Runs all your applications Ÿ Stores all your information Ÿ Highly scalable, available, reliable Ÿ Secure Ÿ Easy to manage – – Make individual systems self-managing Manage thousands of servers at once 10 G

Oracle Database 10 G – The First Database Designed for the Grid

Orders of MAGNITUDE… ~354 NEW 10 g features * @5 slides / feature * @2 minutes /slide = 4. 5 DAYs [ 9 hour/day ]

Oracle Database 10 G – Database for the Grid Storage for All Your Data Real Application Clusters High Availability Ease of Management Data Provisioning across Grid Business Intelligence on the Grid Application Development on the Grid

Oracle Database 10 G – Align Storage with the Business Problem: Islands of storage – “My storage is 50% utilized and growing 30% a year” CRM ERP DW

Oracle Database 10 G – Align Storage with the Business Problem: Islands of storage – “My storage is 50% utilized and growing 30% a year” Solution: Groups of standard, modular disks – – Consolidated, Networked Storage Dynamically Provision

Oracle Grid Storage Management Highly Available and Low Cost Oracle Automatic Storage Management – – – Manages disk storage groups Mirrors, Stripes, Re-balances Huge reduction in labor cost Built-In Data Protection at Lowest Cost – – – Disk Based Backup and Recovery Flashback in Time Site Recovery Automatic Storage Management Disk Based Backup & Recovery

Automatic Storage Management – Dynamically Provision and Tune Storage Portable, high performance file system Eliminates need for conventional file system and volume manager Automatic mirroring Automatic I/O tuning – Stripes data across disks to balance load

The Operational Stack ASM TODAY Tablespace Files 0010 0010 0010 Tablespace Files File System Logical Vols Disks ASM Disk Group “The best way to lower mgmt costs is to remove complexity”

ASM Disk Groups A pool of disks managed as a logical unit Partitions total disk space into uniform sized megabyte units ASM spreads each file evenly across all disks in a disk group Coarse or fine grain striping based on file type Disk groups integrated with Oracle Managed Files Disk Group

ASM Disk Groups • Administer disk groups not files • Number of disk groups remains constant while number of files and disks continually increases Fast Disk Group Slow Disk Group

Mirroring with ASM Failure Groups Controller 1 Controller 2 Storage resources organized into Disk Groups and Failure Groups A Disk Group is a collection of disks managed as a logical unit in which ASM files are stored Disk Groups assigned by DBAs A Failure Group is a set of disks sharing a common resource whose failure needs to be tolerated – Failure Group 1 Failure Group 2 Disk Group 1 Redundant copies of an extent are stored in separate Failure Groups assigned by DBAs or automatically by ASM

Automatic Storage Management – Lowest Labor Cost 8 7 7 6 6 6 5 4 2 2 0 0

ASM Delivers Great Performance with no Manual Tuning 22, 648 20, 590

Automatic Storage Management Mission Critical, Low Cost Storage for Enterprise Grids Mission-critical – – – Integrated mirroring Add/drop disk online Best I/O performance Easy – – Automatic I/O Tuning Up to 50% less DBA/Sys Admin work Low Cost – – Works well with inexpensive disks Better storage utilization

Oracle DB 10 G Stores All Your Data Complete Integrated Relational Characters, Numbers and Dates Oracle Text management and search Oracle inter. Media Multimedia management Oracle Locator Location and Proximity Searching XML DB Integrated Native XML Database OCS Files Low-cost and Easy 41

Oracle DB 10 G ULDB - Stores ALL Your Database size limit raised to millions of Terabytes (8 Exabytes) Ultra Large Data Files – Terabytes in single file Unlimited size LOB columns – Terabytes Automatic Storage Management removes file system limits

Align Processing with the Business Problem: Islands of computation – “My servers are 15% utilized“ CRM ERP DW

Align Processing with the Business Problem: Islands of computation – “My servers are 15% utilized“ Solution: Groups of industry standard servers – – – Lowest cost, highest performance Capacity on demand Not Self-healing, Disposable

Oracle Database 10 G RAC Capacity on Demand for the Grid Only Cluster Database that runs Real Applications and ERP Scales Highly Available Runs on standard, low cost servers Proven – – Hundreds of customers Certified with leading apps CRM DW

Automatic Workload Management Order Entry Spare Supply Chain Normal Server Allocation

Automatic Workload Management Order Entry Supply Chain End of Quarter

Oracle Database 10 G RAC Complete, Integrated Clusterware Complete Oracle cluster software solution Single-vendor support Low Cost – – No need to purchase additional software Easy to install, manage High quality and functionality across all platforms Common event and management API’s Support for third-party clusterware Services Framework Cluster Control/Recovery Messaging and Locking Connectivity

Benefits of Integrated Clusterware Lower software cost Easy – – Deploys in hours not days Single integrated target for cluster management provides improved single system image Less Risk – – Same high functionality and quality across platforms Single vendor support

Automatic Server Provisioning Push-button add/drop server to cluster Hands-free allocation and re-allocation of servers to services – – Automatic routing of service requests to appropriate server with lowest load On server failure, automatic re-allocation of surviving servers to services Works across all platforms

Oracle RAC 10 G - Only Solution for Enterprise Grids Mission Critical Quality of Service on Industry Standard, Low Cost Servers Complete, Integrated Oracle Clusterware Runs all Applications Provides Capacity on Demand RAC Made Easy for Everyone Automatic Server Provisioning

Low Cost Fault Tolerance Computer Failures Unplanned Downtime Planned Downtime Data Failures System Changes Data Changes

Low Cost Fault Tolerance Computer Failures Unplanned Downtime Planned Downtime Data Failures System Changes Data Changes Oracle 10 G RAC Integrated clusterware – Integrated, less moving parts, better tested Faster failover between servers – Single digit seconds

New Economics for Data Protection & Recovery Computer Failures Unplanned Downtime Disk-Based Recovery Data Failures Trade cheap disk space for expensive downtime Planned Downtime System Changes Data Changes 56

Flashback Database Disk Write New Block Version Old Block Version New strategy for point-in-time recovery Flashback Log captures old versions of changed blocks – Flashback Log Like a “Rewind” button for the Database – – Think of it as a continuous backup Replay log to restore DB to time Restores just changed blocks It’s fast - recovers in minutes, not hours It’s easy - single command restore – SQL> Flashback Database to ‘ 2: 05 PM’

Flash Backup Fully automatic diskbased backup and recovery – Set and Forget Nightly incremental backup rolls forward recovery area backup – Database Area Recovery Area Tape – Nightly Apply of Incremental Backup Weekly Archive to Tape Changed blocks are tracked in production DB Dramatically faster (20 x) Use low cost ATA disk array for recovery area

Oracle Database 10 G Highest Data Protection for Lowest Cost. Data Guard Redo Shipping Flash Backup Flashback ASM Mirroring Storage Failure Protection Flashback Logs Human Error Protection On Disk Backups Corruption Protection Site Failure Protection

No Cost System Changes Computer Failures Unplanned Downtime Planned Downtime Data Failures System Changes Goal Allow any change to the system with no downtime Online Reconfiguration Rolling Upgrades Data Changes 60

Oracle 10 G High Availability Features Backup and Recovery (Cont) – Automated Disk– – – – – Based Backup and Recovery Drop Database RMAN Database Deregistration Backup of Standby Control File Automated TSPITR Instantiation Simplified Recovery Manager Cataloging of Backup Files Automated Channel Failover for Backup and Restore Automated File Creation During Recovery Simplified Backups to Disk Proxy Copy Backup of Archivelogs – – – Incrementally Updated Backups Simplified Recovery Through Resetlogs Restore Tolerates Corrupt or Missing Backups Full Database Begin Backup Command Change-Aware Incremental Backups Data Guard – – Data Guard Broker Support for RAC Automated Log. Miner Configuration Log Miner Support for Index-Organized Tables Secured Redo Transmission Data Guard (Cont) – – – Fine-Grained Supplemental Logging Named Data Guard Configurations Simplified Zero Data Loss for Data Guard SQL Apply Zero Downtime Instantiation for SQL Apply Real Time Apply Redo Data and Archivelog Compression Flashback – – – – Flashback Database Flashback Reinstantiation Flashback Standby Database Flashback Table Flashback Row History Flashback Drop Flashback Transaction History Online Operations – – Enhanced Online Redefinition Improved Handling of DDL Locks on Busy Tables Signature-Based Dependency Tracking Using Synonyms Rolling Upgrades with Data Guard SQL Apply

Oracle Database 10 G Ease of Management Self-Managing Database OEM Grid Control – – Grid-wide operations Scale from one to hundreds of systems with little incremental cost

Business Challenge – How to Scale DBA’s to the Grid ? Installation 6% Creation & Configuration 12 % Others 15% Software Maintenance 6% Data Loading 6% Ongoing System Management 55% Source: IOUG 2001 DBA Survey

Oracle 10 G System Management – Built-In Intelligent Infrastructure Automatic Workload Repository – Automatically collects statistics, SQL workload, Feature usage Automatic Maintenance Tasks – Pre-packaged, resource controlled Server-Generated Alerts – Out-of-the-box, Push vs. Pull, Just-in-time

Oracle 10 G System Management – Automatic SGA Management Online Users Buffer Cache Large Batch Jobs Buffer Cache Large Pool SQL Cache Java Pool sort Only 2 memory parameters Advisor helps set parameters Automatically resizes with changes in SGA Pool workload Maximize usage PGA Pool available memor

Oracle 10 G System Management – Self Optimizing SQL Management Oracle Query Optimizer – Proven Technology – – Comprehensive set of access paths, adaptive search strategy All cost-based transformations Preconfigured task to collect object and system statistics If no statistics available, are collected at parse-time Automatic memory allocations, automatic degree of parallelism Automatic identification and capture of high-load SQL – – – Automatic SQL Tuning Automatic SQL Analysis SQL Access Advisor

Oracle 10 G System Management – Self Optimizing SQL Management Packaged Applications High-load SQL Custom Applications Optimizer Auto SQL Tuning Auto SQL Analysis Access Advisor SQL Profile SQL Advice Indexes & MVs Packaged Applications Custom Applications Well-tuned SQL Automated capture and identification of high-load SQL Automatic SQL Tuning Automatic SQL Analysis SQL Access Advisor

Oracle 10 G System Management – Automatic Database Diagnostic Monitor Performance expert in a box Automatically provides databasewide performance diagnosis, including RAC Pinpoints root cause and non-problem areas Runs proactively

Enterprise Manager 10 G Grid Control Management that Scales to the Grid Ÿ Central management for the complete platform Ÿ Dramatically lower operations costs Ÿ Application service level management Ÿ Manage one or many systems with little incremental cost

Scalable Software Maintenance – Discover and Analyze Configurations Complete inventory of all Oracle software – – Versions Patch levels Oracle product configuration details Search and compare configurations Change tracking Reference configurations

Scalable Software Maintenance - Automa Reduce manual labor in software life-cycle – From hours to minutes Automate mass provisioning of reference systems 1 Select Software (and Instances) to Clone to Selected Targets 2 3 Update Inventory

Scalable Software Maintenance - Automa Real-time discovery of new patches – Security patch rapid deployment dramatically reduces vulnerabi Automatic staging and application – From hours to minutes Rolling RAC upgrade 2 Determine Applicability 3 Apply Patch 4 1 Patch Published Update Inventory

Oracle 10 G Manageability Features Infrastructure – – – Server Configuration Easy Oracle. JVM Monitoring SYSAUX Tablespace Enhanced Wait Model Database Features Usage Tracking Enhanced Database Time Model Top Consumers Performance Monitoring & Diagnostic JDBC: End-to-end Java/J 2 EE Tracing SQLJ: End-to-end Java/J 2 EE Tracing Automated Routine Administration Tasks Proactive Server-based Alerts and Notifications Database Statistics and Workload Respository Threshold-Based Alerts – – – Instance Tuning Automated Storage Management Configuration Automated RAC Services Configuration Simplified Upgrade for RAC and OPS Databases Automated Enterprise Manager Configuration Automated Portable Clusterware Installation Automated Configuration of Recovery Area Out-of-the-box LDAP Configuration Simplified Initialization Parameters Easy Upgrade Information Tool Simplified Database Install User Default Tablespace – – – Application Tuning User-Initiated Buffer Cache – SQLAccess Advisor Flushing – Materialized View Tuning Database Resource Manager API - Adaptive Consumer Group – SQL Tuning Advisor Mapping – Enhanced SQLAccess Database Resource Manager Advisor - Fixed CPU Quota – Automatic Optimizer New Performance Overview Statistics Collection Charts in Oracle Enterprise Backup and Recovery Manager – Enhanced RMAN Reporting Improved SQL Reporting – Backup Compression Using Oracle Enterprise Manager – Bounded Backup Window Integration of Resource – Manage RMAN Scripts Manager and Profiles – Recovery Area Full Alert Automated Checkpoint Tuning Storage Management Transaction Rollback & – Multiple Default Temporary Recovery Monitoring Tablespace Support for Database Performance SQL Operations Analyzer – Automated Storage Redo Logfile Sizing Advisor Management Automated SGA Memory – Rename Tablespace Tuning

Oracle 10 G Manageability Features (continued) Space, Object, Transaction Mgmt Back Up Directory Naming Network Management – – – – – Entries to Local Naming File Dynamic Connection Manager Configuration Easy Connect Naming Method Easy OCI/JDBC Install Improved Network Outage Detection Automated LDAP Discovery for Clients Improved Connection Manager Access Rules Automated Shared Server Configuration Simplified Shared Server Configuration Parameters – – – Database Utilities Automatic Undo Retention Tuning Segment Shrink Advisor Segment Size Estimation Online Segment Shrink Proactive Tablespace Management Undo Advisor – – – – Scheduler SQL*Plus - SPOOL CREATE, REPLACE, and APPEND Options SQL*Plus - Show Recycle Bin SQL*Plus DBMS_OUTPUT After SELECT SQL*Plus - SET SQLPROMPT Runtime Variable Substitution SQL*Plus COMPATIBILITY Command Line Option SQL*Plus - Run glogin. sql and login. sql After Each CONNECT i. SQL*Plus Input Prompting – – – – – Core Scheduler Features Usability and Manageability Monitoring Recovery Support for Jobs in a Clustered Environment Job Processing ILMS Support Increased Throughput Redo Minimization Dynamic Slave Pool

Transportable Tablespaces – Fastest Way to Provision Data Oracle can unplug and plug database data files – – – Move and share data without unload and reload Plug/unplug performance independent of tablespace size Mount read-only tablespaces on multiple databases New: Now Works Cross-Platform! 24

Oracle 10 G Data Pump High performance import and export – – 60% faster than 9 i export (single thread) 15 x-20 x faster than 9 i import (single thread) Scales with parallel threads Network transfer data between databases with no intermediate representation

Oracle Streams moves or copies tablespaces faster than FTP Detach, move, attach with one command Same platform or cross platform

Oracle Streams moves or copies tablespaces faster than FTP Detach, move, attach with one command Optionally stream delta updates Migrate to the Grid with the self-propelled database Same platform or cross platform

Oracle Database 10 G– Database for the Grid Storage for All Your Data Real Application Clusters High Availability Ease of Management Data Provisioning across Grid Business Intelligence on the Grid Application Development on the Grid

Business Intelligence on the Grid Lower Cost – – Leverage 10 G hardware, software, labor savings Manage millions of terabytes Intelligence when you need it – Real-time data feeds and integrated BI capabilities More value from your data – Additional integrated BI capabilities

Managing Large Volumes of Data Partitioning and parallelism are crucial for VLDB Partitioning provides ‘incremental’ operations for: – – WORK SMARTER Data loading, Indexing, Referential Integrity Backup and Recovery Queries Parallelism for all operations – – WORK HARDER DBA operations: loading, index-creation, table-creation, datamodification, backup and recovery End-user operations: Queries Unbounded scalability: Real Application Clusters

Partitioning - Minimal Unit of Work Intelligent usage of partitioning information is key success factor for availability – – – Partition Pruning Backup and Recovery Read-Write versus Read-Only order table jan 99 feb 99 mar 99 apr 99 may 99

Partitioning - Rolling Window Partition level management – – – Range, Composite (range + hash), List On-line addition and removal of partitions Data management operations (loading, index builds) Improved availability – Localized disk failures, backup and recovery Add order table jan 99 feb 99 mar 99 apr 99 Drop Local Index Other data is not affected may 99

Table Compression increases: – – I/O-subsystem capacity I/O throughput query scan performance buffer cache capacity Table Compression: – – reduces cost of ownership is easy to use requires little or no table definition changes is transparent to applications

Table Compression: What is it? Tables can be compressed – – Compression can also be specified at the partition level Indexes and index-organized tables are not compressed Typical compression ratios are 3: 1 - 6: 1 – – Compression is dependent upon the actual data Compression algorithm based on removing data redundancy All DDL/DML commands are supported on compressed tables

Oracle Parallel Query - Scanning Scanner #1 Scanner #2 Scanner #3 . . . Data is Partitioned into Granules (block range or partition) Each Scanner is Assigned Multiple Granules No two scanners ever contend for the same granule Granules are assigned so that the Load is Balanced Across all Scanners Dynamic Granules

10 G Real Time Warehouse Asynchronous CDC Archived log files Based on Streams DW Tables Logical Change Data Transform SQL, PL/SQL, Java OLTP DB SQL interface to change data Publish/subscribe paradigm Parallel access to log files, leveraging Oracle Streams Parallel transformation of data

Oracle 10 G Business Intelligence Features Real Time Data Warehousing – – – – – VLDB Asynchronous Change Data Capture Cross-Platform Transportable Tablespaces Enhanced Table Functions External Tables Unload Enhanced MERGE Functionality Data Pump Export and Import Utilities Parallel Data Pump Export and Import SQL*Loader Direct Path Load Support for ROWID Datatype SQL*Loader Direct Path Load Support for VARRAY Datatype SQL*Loader Direct Path Load Support for XMLType Tables – – – – Summary Management Bigfile Tablespace Enhanced Partition Management in Enterprise Manager Global Partitioned Indexes - Hash Partitioning Partitioned Index. Organized Tables - List Partitioning Partitioned Index. Organized Tables - LOB Support Partitioned Index. Organized Tables - Global Index Maintenance Enhanced Bitmap Index Performance and Space Management Local Partitioned Indexes Manageability Improvements – – – – Summary Management OLAP Query Performance Improvements Summary Management Enhanced Partition-aware Materialized View Refresh Summary Management EXPLAIN PLAN Shows Materialized View Access Summary Management Enhanced Dimensions Summary Management Nested Materialized View Refresh Summary Management Enhanced PCT Refresh Summary Management Query Rewrite Uses Multiple Materialized OLAP – – – – – Parallel AGGREGATE Command Parallel SQL IMPORT Command PL/SQL Creation of Analytic Workspaces Intra-Dimensional (Attribute) Aggregation Enhanced Composite Dimensions Indexing PL/SQL OLAP Measure Calculation Definition Complete Analytical Workspace Management Multi-Writer Support XML Interface for Analytic Workspace

Oracle 10 G Business Intelligence Features (Continued) Data Mining – – – – – Bio-informatics – DOUBLE and FLOAT Frequent Itemsets Datatypes Attribute Importance – BLAST Queries Algorithms – Statistical Functions Enhanced Adaptive Bayes – Document Clustering Network – Document Clustering Non. JSR-73 RI & TCK - Java negative Matrix Data Mining Factorization Multi-User Access Control – Document Clustering Neural Nets Complete Oracle Data Mining Management – Document Named Entity Extraction Enhanced Model Seeker – Support Vector Machines PMML Producers / – Taxonomy Builder Consumers SQL Analytics Enhanced Data – Grouped Table Outer Join Preprocessing – Increased Number of Data Mining Rapid Aggregates per Query Application Development – SQL Interrow Calculations – Upsert Through SQL Interrow Calculations

Application Development on the Grid HTML DB – Low Cost, Hosted, Web Based Development Environment Improved PL/SQL Performance Database Web Services

HTML DB and the Grid - Business Problem Departmental and LOB data sharing and information tracking Lots and lots of desktop databases Fragmented Inaccurate Untimely Vulnerable

HTML DB – Perfect for the Grid Productivity of a Desktop Database Infrastructure of an Enterprise Database Built for the Web Leverages the Grid

Oracle Database 10 G Half the Cost – – – Low cost hardware with high utilization Integrated software stack Self-managing Highest Quality of Service – Highest Performance, Scalability, Availability, Reliability, Security Easy to Align with Business Priorities

Oracle Database 10 g Performance Metrics PLSQL up to 2 x Table Scans up to 2 x SQL Profile Tuning huge Floating point math up to 10 x Bulk LOB Update up to 3 x Import up to 15 x Export up to 35% Incremental backup up 10 x Parallel media recovery 2 -4 x Backup compression 17 x Infiniband interconnect ½ latency, 2 x block transfer TPC-C – – Best absolute and best on 4 way Intel +28% on same hardware

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