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© 2009 Oracle Corporation
Oracle Database Strategy Oracle Database 11g
Charlie Garry, Director, Product Management Oracle Server Technologies
© 2009 Oracle Corporation
DO MORE WITH LESS
© 2009 Oracle Corporation
DO MORE WITH MORE
© 2009 Oracle Corporation
MORE SERVERS
© 2009 Oracle Corporation
MORE STORAGE
© 2009 Oracle Corporation
MORE SOFTWARE LICENSES
© 2009 Oracle Corporation
MORE COST
© 2009 Oracle Corporation
MORE COMPLEXITY
© 2009 Oracle Corporation
WHAT MUST BE DONE?
© 2009 Oracle Corporation
SIMPLIFY
© 2009 Oracle Corporation
FEWER THINGS TO MANAGE
© 2009 Oracle Corporation
FEWER KINDS OF THINGS
© 2009 Oracle Corporation
CURRENT COMPLEXITY
• DIFFICULT AND EXPENSIVE TO SCALE
• POOR UTILIZATION
• EXPENSIVE TO MANAGE
• RISKY TO CHANGE
Middleware
Database
Storage
Dedicated Stacks
© 2009 Oracle Corporation
THE SHARED INFRASTRUCTURE Virtualizes and Pools IT Resources
•Sized for peak load•Difficult to Scale•Expensive to Manage
•Pools of shared resources•Re-distribute resources as needed•Cost efficient
© 2009 Oracle Corporation
Oracle Database 11g Release 2Simplified Grid Provisioning
• New intelligent installer - 40% fewer steps to install RAC• SCAN - Single cluster-wide alias for database connections• Nodes can be easily repurposed
© 2009 Oracle Corporation
Back Office Front Office Depart/LOB Free
© 2009 Oracle Corporation
Consolidating All Your Data
Images
© 2009 Oracle Corporation
Oracle Secure FilesConsolidate Unstructured Data On the Grid
Read Performance Write Performance
0.01 0.1 1 10 100
Mb
/Se
c
0.01 0.1 1 10 100
Mb
/Se
c
File Size (Mb) File Size (Mb)
Secure FilesLinux Files
Secure FilesLinux Files
© 2009 Oracle Corporation
STORAGE CONSOLIDATION ASM CLUSTER FILE SYSTEM
• ASM supports ALL data– Database files– File systems: ACFS, 3rd-party file systems– Shared Clusterware files: OCR and Voting disk now stored
in ASM
New in 11.2
DB DatafilesDB Datafiles OCR and Voting FilesOCR and Voting Files Oracle BinariesOracle Binaries 3rd Party File Systems3rd Party File Systems
Automatic Storage Management (ASM)
File SystemsApplicationsDatabases
© 2009 Oracle Corporation
IMPROVE UTILIZATION RATES
© 2009 Oracle Corporation
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
$400,000
The Price Of CPU Underutilization
5% 20%15%10% 30% 40% 50% 60% 70%
Average CPU Utilization Rate
Act
ual
So
ftw
are
Co
st P
er
CP
U
Purchase Price: $20K Per Processor
Underutilized
Premium
The Price of Underutilized Servers
© 2009 Oracle Corporation
Grid Automated Quality of Service
Resource (CPU)
Sales Pools
Most Important Least Important
Search Pools BI Pools
EMEANA
APAC
Response Time Objectives
Storage
J2EE
Web
DB
© 2009 Oracle Corporation
48 TB of Raw Storage Purchased at $5/GB
Storage Utilization Rate
Price of Storage Underutilization
$25
$20
$17
$15$13
0
5
10
15
20
25
Use
d C
apac
ity
(TB
)
$0
$5
$10
$15
$20
$25
$30
Act
ual
Co
st P
er G
B
40% 35% 30% 25% 20%
The Price of Underutilized Storage
© 2009 Oracle Corporation
STORAGE UTILIZATIONOPTIMAL DISK PLACEMENT
• AUTOMATIC STORAGE MANAGEMENT– DESIGNATE DATA
AS HOT or COLD
Infrequently Accessed
Data
Infrequently Accessed
Data
Frequently Accessed
Data
Frequently Accessed
Data
© 2009 Oracle Corporation – Proprietary and Confidential
New with
11.2
© 2009 Oracle Corporation
STORAGE UTILIZATION ASM GROUPS: TIERED STORAGE
ORDERS TABLE (7 years)
2010 2006+2007
$25/GB <$1/GB5% Active 35% Less Active 60% Historical
ASM Instance
ASM Group 1 ASM Group 2 ASM Group 3
© 2009 Oracle Corporation
NON-TIERED STORAGE TIERED STORAGESTORAGE
TYPETOTAL
CAPACITY GB
PRICE PER GB
TOTAL STORAGE TYPE
TOTAL CAPACITY
GB
PRICE PER GB
TOTAL
High-End 50,000 $25 1,250,000 High-End 2,500 $25 $62,500
Mid-Tier 17,500 $7 $122,500
JBOD 30,000 $1 30,000
Totals 50,000 $25 1,250,000 50,000 $4.30 $215,000
Tiered Approach is 83% Cheaper
STORAGE UTILIZATION ASM GROUPS: TIERED STORAGE
© 2009 Oracle Corporation
Optimize I/O PerformanceAdvanced 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
Compression4XUp To
© 2009 Oracle Corporation
© 2009 Oracle Corporation
OLTP Table Compression Process
Initially Uncompressed
Block
Compressed Block
Partially Compressed
Block
Compressed Block
Empty
Block
Legend
Header Data
Free Space
Uncompressed Data
Compressed Data
© 2009 Oracle Corporation
Block-Level Batch Compression
• Patent pending algorithm minimizes performance overhead and maximizes compression
• Individual INSERT and UPDATEs do not cause recompression• Compression cost is amortized over several DML operations• Block-level (Local) compression keeps up with frequent data changes
in OLTP environments– Others use static, fixed size dictionary table thereby compromising
compression benefits
• Extends industry standard compression algorithm to databases– Compression utilities such as GZIP and BZ2 use similar adaptive, block
level compression
© 2009 Oracle Corporation
Exadata Smart StorageBreaks Data Bandwidth and Random I/O Bottleneck
• Oracle addresses data bandwidth bottleneck 4 ways
– Massively parallel storage grid of high performance Exadata storage servers (cells).
– Data bandwidth scales with data volume– Data intensive processing runs in Exadata storage.
– Queries run in storage as data streams from disk, offloading database server CPUs
– Exadata Smart Flash Cache Increase random I/Os by factor of 20X
– Columnar compression reduces data volume up to 10x
– Exadata Hybrid Columnar Compression provides 10x lower cost, 10x higher performance
Exadata Storage Cells
New in 11.2
© 2009 Oracle Corporation
• Data stored by columnand then compressed
• Useful for data that is bulk loaded or moved
• Query mode for data warehousing• Typical 10X compression ratios• Scans improve accordingly
• Archival mode for old data• Typical 15X up to 50X compression
ratios
Oracle Exadata Storage ServerHybrid Columnar Compression
50XUp To
© 2009 Oracle Corporation
© 2009 Oracle Corporation
10 10 10 1116 19 19 19 20 21
29
43
05
101520253035404550
Siz
e R
edu
ctio
n F
acto
r b
y T
able
OLTP Compression (avg=3.3)
Query Compression (avg=14.6)
Archive Compression (avg=22.6)
Real-World Compression RatiosOracle Production E-Business Suite Tables
• Columnar compression ratios• Query = 14.6X• Archive = 22.6X• Vary by application and table
5252
© 2009 Oracle Corporation
LOWER SUPPORT COSTS
© 2009 Oracle Corporation
CONSOLIDATED MANAGEMENTENTERPRISE MANAGER GRID CONTROL
• RATIONALIZED MANAGEMENT OF A RATIONALIZED PLATFORM
• IMPROVED PROCESS MATURITY– MORE REPEATABILITY
– MORE AUTOMATION
• MANAGEMENT COST AMORTIZED OVER MULTIPLE APPLICATIONS
Oracle Clusterware
Oracle Real Application Clusters
Automatic Storage Management
Ora
cle
Ent
erpr
ise
Man
ager
Oracle Grid Components
Oracle Clusterware
Oracle Real Application Clusters
Automatic Storage Management
Ora
cle
Ent
erpr
ise
Man
ager
Oracle Clusterware
Oracle Real Application Clusters
Automatic Storage Management
Ora
cle
Ent
erpr
ise
Man
ager
Oracle Grid Components
© 2009 Oracle Corporation
Managing Complexity Automated Self-management
Automated:• Storage• Memory• Statistics• SQL tuning• Backup and Recovery
Advisory:• Indexing• Partitioning• Compression• Availability• Data Recovery
© 2009 Oracle Corporation
© 2009 Oracle Corporation
IMPROVE AVAILABILITY
© 2009 Oracle Corporation
Oracle Maximum Availability ArchitectureEliminate the cost of planned downtime
Add/RemoveStorage
Redefine andReorganize
TablesOnline
Production TestingReporting
Add/RemoveNodes and CPUS
Undo Human Error
OnlineUpgrades Online Patching
© 2009 Oracle Corporation
ADAPT TO CHANGE
© 2009 Oracle Corporation
TECHNOLOGIC OR ECONOMIC
© 2009 Oracle Corporation
FASTER
© 2009 Oracle Corporation
WITH LESS RISK
© 2009 Oracle Corporation
……
ClientClient
…Client
Capture DB Workload
Make Change Safe - Realistic Testing with Database Replay
• Recreate actual production database workload in test environment
• No test development required
• Replay workload in test with production timing
• Analyze & fix issues before production
Middle Tier
Storage
Oracle DB
Replay DB Workload
Production Test
Test migration to RAC
© 2009 Oracle Corporation
Make Change Safe – Find Regressed SQL with SQL Performance Analyzer
© 2009 Oracle Corporation
SIMPLIFY
© 2009 Oracle Corporation
Exadata Storage Server Grid• 21 GB/sec disk bandwidth
• 50 GB/sec flash bandwidth
• 1 million I/Os per second
RAC Database Server Grid• Millions of transactions
per minute
• Tens of millions of queries per minute
• Billions of rows per minute
InfiniBand Network• 880 Gb/sec aggregate
throughput
Exadata Storage Server Grid• 21 GB/sec disk bandwidth
• 50 GB/sec flash bandwidth
• 1 million I/Os per second
RAC Database Server Grid• Millions of transactions
per minute
• Tens of millions of queries per minute
• Billions of rows per minute
InfiniBand Network• 880 Gb/sec aggregate
throughput
Full Rack
Half Rack
Quarter Rack
Full Rack
Half Rack
Quarter Rack
The Fastest Way to the Grid
© 2009 Oracle Corporation
Your IT Information Infrastructure In a Box
• Consolidation mixes many different workloads in one system– Warehouse oriented bulk data processing– OLTP oriented random updates– Multimedia oriented streaming files
• The Oracle Database Machine handles any combination of workloads with extreme performance– And predictable response times
• Rationalize and Consolidate on Oracle Grid
ERP
CRM
Warehouse
Data Mart
HR
© 2009 Oracle Corporation
Oracle Database Strategy Oracle Database Oracle Database 11g and Beyond
• Simplify the information infrastructure– Consolidate– Rationalize
• Reduce Cost– Improve utilization of the entire infrastructure– Reduce operational expense
• Reduce Risk of Change– Provision fixes– Accurately test changes– Rolling Upgrades
© 2009 Oracle Corporation
Oracle Database Strategy Oracle Database 11g
Charlie Garry, Director, Product Management Oracle Server Technologies