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Larry Ellison
Chief Executive Officer, Oracle
Oracle Confidential – Internal/Restricted/Highly RestrictedCopyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Oracle Database In-Memory
Powering the Real-Time Enterprise
2 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Database
In-Memory
Option
Powering the Real-Time
Enterprise
Available in July
3 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Database In-Memory Option: Goals
 100X Faster Queries: Real-Time Analytics
• Instantaneous Queries on OLTP Database or Data Warehouse
 2x Faster OLTP
• Insert rows 3x to 4x faster
 Transparent: No application changes
• Minutes to Implement
4 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle 12c Stores Data in Both Formats Simultaneously
Optimizing Transaction and Query Performance
Row Format Databases versus Column Format Databases
Row
 Transactions run faster on row format
– Example: insert or query a sales order
– Fast processing of few rows, many columns
Column
 Analytics run faster on column format
– Example: report on sales totals by region
– Fast accessing of few columns, many rows
ORDER
SALES
SALESREGION
5 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
 BOTH row and column
formats for same data/table
 Simultaneously active and
transactionally consistent
 100X Faster Analytics
in-memory column format
 2X faster OLTP: row format
Innovation: Dual Format In-Memory Database
Column
Format
Memory
Row
Format
Memory
AnalyticsOLTP Sales Sales
Sales
6 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory Column Format
Pure In-Memory
Pure Columnar
 2X to 20X compression: Faster Scans
 No data change logging: Faster OLTP
 Enabled at table or partition level
 Available on all hardware platforms
Sales
Sales
7 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Scans Billions of Rows per Second per CPU Core
SIMD
Compare all
values in 1
cycle
Vector
Compare
all values
in 1 cycle
Load
multiple
Region
values
Vector
Register
In-Memory Column Store
Sales
Example: Find all sales in region of CA
“CA”
>100X
Faster
• Each CPU core scans
local in-memory columns
 Scans use super fast
SIMD vector instructions
 Billions of rows/sec
scan rate per CPU core
CPU
R
E
G
I
O
N
8 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
10x Faster Joining and Combining Data
SalesStores
Type=outlet
Example: Find total sales in outlet stores
Storeid
in
15,38,64
S
T
O
R
E
I
D
A
M
O
U
N
T
 Converts join processing
into fast column scans
 Joins tables 10x faster
Sum
S
T
O
R
E
I
D
T
Y
P
E
9 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Generate Reports Instantly
In-Memory
Report
Outline
Example: Report sales of footwear in
outlet stores
Products
Stores
Sales
Footwear
Sales
 Dynamically creates
in-memory report outline
 Then report outline filled-in
during fast fact scan
 Reports 20x faster without
predefined cubes
Outlets
Footwear
10 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
OLTP is Slowed by Analytic Indexes
Table
1 to 3
OLTP
Indexes
10 to 20
Analytics
Indexes
 Most OLTP Indexes (e.g. ERP)
are only used for analytic
queries
 Inserting one row into a table
requires updating 10-20
analytic indexes: Slow!
 Indexes only speed up
anticipated queries & reports
11 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Column Store Replaces Analytic Indexes
Table
1 to 3
OLTP
Indexes
 100x Faster analytics
 Works on any columns
 Better for ad-hoc analytics
 Less tuning required
• 2x Faster OLTP and Batch
• Column store not logged
• Row Insert cost is lower
In-Memory
Column Store
12 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Scale-Out In-Memory Database to Any Size
In Memory
Column Store
 Scale-Out across servers to
grow memory and CPUs
 In-Memory queries parallelized
across servers to access local
column data
 Direct-to-wire InfiniBand
protocol speeds messaging
In Memory
Column Store
In Memory
Column Store
In Memory
Column Store
13 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
In-Memory Speed + Capacity of Low Cost Disk
 Size not limited by memory
 Data transparently moves
between tiers
 Each tier has specialized
algorithms & compression
Speed of DRAM
I/Os of Flash
Cost of Disk DISK
PCI
FLASH
DRAM
Cold Data
Hottest Data
Active Data
14 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Scale-Up for Maximum In-Memory Performance
 Scale-Up on large SMPs
 SMP scaling removes
overhead of distributing
queries across servers
 Memory interconnect far
faster than any network
M6-32
Big Memory Machine
32 TB DRAM
32 Socket, 384 Cores
3 Terabyte/sec Bandwidth
15 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory: Extreme Availability
 Pure In-Memory format does not
change  Oracle’s  storage format,
logging, backup, recovery, etc.
 All  Oracle’s  mature availability
technologies work transparently
 Protection from all failures
 Node, site, corruption,
human error, etc.
RAC
ASM
RMAN
Data Guard & GoldenGate
16 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory: Unique Fault Tolerance
 Similar to storage mirroring
 Duplicate in-memory
columns on another node
• Enabled per table/partition
• Application transparent
 Downtime eliminated by
using duplicate after failure
17 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory: Implement in Minutes
1. Configure Memory Capacity
 inmemory_size = XXX GB
2. Configure tables or partitions to be in memory
 alter  table  |  partition    …    inmemory;
3. Drop analytic indexes to speed up OLTP
18 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory Requires Zero Application Changes
Full Functionality - No restrictions on SQL
Easy to Implement - No migration of data
Fully Compatible - All existing applications run unchanged
Fully Multitenant - Oracle In-Memory is Cloud Ready
Uniquely Achieves All In-Memory Benefits With No Application Changes
19 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle
Applications
From Batch to Real-Time
With In-Memory and
Engineered Systems
Oracle Database In-Memory
Oracle Applications
20 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Real-Time Enterprise
 Data Driven – Rapidly make decisions
based on real-time data
 Agile – Respond quickly to change
 Efficient – Continually improve
processes and profitability
Real-Time Enterprise
AGI
LE
EFFICIENT
DATA-
DRIVEN
AGILE
21 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory Cost Management
 Adjust product mix, pricing, and marketing
investments to maximize profits in real-time
 Recalculate cost of every component in
inventory, work-in-process, in-transit
shipments, and finished good
 Fast analysis of cost differences across
manufacturing locations for make or buy
decisions • 1.9 Billion Cost Rows
• 13.8 Million Items
• 14 Level BOM
From 58 Hours to 13.5 Minutes
257X Faster
22 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
PeopleSoft In-Memory Financial Analyzer
 Iterative financial position analysis
in real-time
 Make earlier decisions for the
financial period
 Speed account reconciliation
 Shorten financial period close
• 290M Ledger Lines
• 250 Business Units
• 7 Step Analysis, Pivot, Drill
From 4.3 Hours to 11.5 Sec
1300X Faster
23 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle In-Memory Transportation Management
 Dispatchers perform real-time
monitoring and rerouting when
en-route exceptions occur
 Benefits of instant rerouting:
 Reduction in empty miles and in Driver
turnaround time
 Improved on-time delivery
 Improved Dispatcher efficiency and
Driver retention
• 145M Status Records
• 60M Shipment Data Records
• 16K Drivers
From 16 Min to Sub-second
1030X Faster
24 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
JD Edwards Sales Order Analysis
 Operational Analysis of sales
orders in real-time
 Find immediate answers to
unanticipated customer sales
questions
 Eliminate batch jobs, data
exports, third-party systems
 1000’s  of  use  cases  across  all  
functional areas
• 104 million sales order lines
From 22.5 Min to Sub-second
1700X Faster
25 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
JD Edwards Customer Receivables Management
 Real-Time receivables summarization
 Balances by customer, line of business,
and currency
 Eliminate multiple queries, batch jobs,
data exports
 Similar use cases for projects,
suppliers, assets, inventory etc.
• 10 million invoice lines
From 244 Min to 4 Secs
3500X Faster
26 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Value Chain Planning
Demantra Promotion Planning
 Marketing Managers want detailed data
when analyzing promotion plans
 Benefits of real-time promotion
analytics:
 Analyze promotion profit and revenue
on real-time basis
 Optimize promotion spend
 Better assess timing and cost impacts
• 1.3 Billion Rows
• Aggregate 36M rows
• 2 week major sell-through report
From 1120 to 11 Seconds
102X Faster
27 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Value Chain Planning
Demantra Consumption Driven Planning
 Daily store-level forecasting and
replenishment requires processing high
volume POS data multiple times a day
 Benefits of real-time planning:
 Consumption and shipment based
forecasting in a single scalable system
 Improved forecast accuracy and
customer service levels at lower cost
• 400 Million Rows
• 1.4 Million SKU Locations
From 12.7 Hours to 56 Minutes
13.5X Faster
28 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Value Chain Planning
Supply Chain Planning and Analytics
 Supply Chain analysts spend hours
processing granular supply and demand
data
 Benefits of real-time planning:
 Planners share business metrics with
analysts  and  VP’s  of  Supply  Chain  real-
time
 Quickly solve supply disruptions and
unexpected demand fluctuations
• 360K Items
• 1.2M Demands, 1M exceptions
• 5.7M KPI records
From 230 to 3 minutes
76X Faster
29 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Siebel Marketing – List Import
 Real-time marketing for large
numbers of prospects
 Rapid processing of marketing data
for campaign launch
 Accelerate import of large
numbers of prospects
 Reduce data-cleansing time
From 1.9 hours to 49 sec
• Import and Cleanse 1 Million Records
140X Faster
30 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Fusion Cloud Financials
Subledger Period Close Exceptions
 Lists all accounting events and
journal entries that fail period
close validation in real-time
 Report is run many times at end of
quarter and is a bottleneck to close
From 10 Minutes to 3 Sec
• 19 Million Ledger Lines
210X Faster
31 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Oracle Fusion Cloud Financials
Sales Pipeline Analytic Report
• Report potential income in
real-time
• Aggregate revenue from
opportunities grouped within each
sales stage for a specific time
period
From 52 Minutes to 24 Sec
• 1.6 million opportunities
• 5.1 million revenue lines
129X Faster
32 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Become a Real-Time Enterprise
Using Oracle Database In-Memory
Real-Time Enterprise
 Data-Driven
• Get immediate answers to any
question with real-time analytics
 Agile
• Eliminate latency with analytics
directly on OLTP data
 Efficient
• Non-disruptively accelerate all
applications
AGI
LE
EFFICIENT
DATA-
DRIVEN
AGILE
33 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Summary: Oracle Database In-Memory
 Extreme Performance: Analytics & OLTP
 Extreme Scale-Out & Scale-Up
 Extreme Availability
 Extreme Simplicity
Powering the Real-Time Enterprise
All In-Memory Benefits With No Application Changes
34 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Larry Ellison Introduces Oracle Database In-Memory

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Larry Ellison Introduces Oracle Database In-Memory

  • 1. Larry Ellison Chief Executive Officer, Oracle Oracle Confidential – Internal/Restricted/Highly RestrictedCopyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Database In-Memory Powering the Real-Time Enterprise
  • 2. 2 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Database In-Memory Option Powering the Real-Time Enterprise Available in July
  • 3. 3 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Database In-Memory Option: Goals  100X Faster Queries: Real-Time Analytics • Instantaneous Queries on OLTP Database or Data Warehouse  2x Faster OLTP • Insert rows 3x to 4x faster  Transparent: No application changes • Minutes to Implement
  • 4. 4 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle 12c Stores Data in Both Formats Simultaneously Optimizing Transaction and Query Performance Row Format Databases versus Column Format Databases Row  Transactions run faster on row format – Example: insert or query a sales order – Fast processing of few rows, many columns Column  Analytics run faster on column format – Example: report on sales totals by region – Fast accessing of few columns, many rows ORDER SALES SALESREGION
  • 5. 5 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.  BOTH row and column formats for same data/table  Simultaneously active and transactionally consistent  100X Faster Analytics in-memory column format  2X faster OLTP: row format Innovation: Dual Format In-Memory Database Column Format Memory Row Format Memory AnalyticsOLTP Sales Sales Sales
  • 6. 6 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Column Format Pure In-Memory Pure Columnar  2X to 20X compression: Faster Scans  No data change logging: Faster OLTP  Enabled at table or partition level  Available on all hardware platforms Sales Sales
  • 7. 7 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scans Billions of Rows per Second per CPU Core SIMD Compare all values in 1 cycle Vector Compare all values in 1 cycle Load multiple Region values Vector Register In-Memory Column Store Sales Example: Find all sales in region of CA “CA” >100X Faster • Each CPU core scans local in-memory columns  Scans use super fast SIMD vector instructions  Billions of rows/sec scan rate per CPU core CPU R E G I O N
  • 8. 8 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. 10x Faster Joining and Combining Data SalesStores Type=outlet Example: Find total sales in outlet stores Storeid in 15,38,64 S T O R E I D A M O U N T  Converts join processing into fast column scans  Joins tables 10x faster Sum S T O R E I D T Y P E
  • 9. 9 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Generate Reports Instantly In-Memory Report Outline Example: Report sales of footwear in outlet stores Products Stores Sales Footwear Sales  Dynamically creates in-memory report outline  Then report outline filled-in during fast fact scan  Reports 20x faster without predefined cubes Outlets Footwear
  • 10. 10 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. OLTP is Slowed by Analytic Indexes Table 1 to 3 OLTP Indexes 10 to 20 Analytics Indexes  Most OLTP Indexes (e.g. ERP) are only used for analytic queries  Inserting one row into a table requires updating 10-20 analytic indexes: Slow!  Indexes only speed up anticipated queries & reports
  • 11. 11 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Column Store Replaces Analytic Indexes Table 1 to 3 OLTP Indexes  100x Faster analytics  Works on any columns  Better for ad-hoc analytics  Less tuning required • 2x Faster OLTP and Batch • Column store not logged • Row Insert cost is lower In-Memory Column Store
  • 12. 12 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scale-Out In-Memory Database to Any Size In Memory Column Store  Scale-Out across servers to grow memory and CPUs  In-Memory queries parallelized across servers to access local column data  Direct-to-wire InfiniBand protocol speeds messaging In Memory Column Store In Memory Column Store In Memory Column Store
  • 13. 13 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. In-Memory Speed + Capacity of Low Cost Disk  Size not limited by memory  Data transparently moves between tiers  Each tier has specialized algorithms & compression Speed of DRAM I/Os of Flash Cost of Disk DISK PCI FLASH DRAM Cold Data Hottest Data Active Data
  • 14. 14 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scale-Up for Maximum In-Memory Performance  Scale-Up on large SMPs  SMP scaling removes overhead of distributing queries across servers  Memory interconnect far faster than any network M6-32 Big Memory Machine 32 TB DRAM 32 Socket, 384 Cores 3 Terabyte/sec Bandwidth
  • 15. 15 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Extreme Availability  Pure In-Memory format does not change  Oracle’s  storage format, logging, backup, recovery, etc.  All  Oracle’s  mature availability technologies work transparently  Protection from all failures  Node, site, corruption, human error, etc. RAC ASM RMAN Data Guard & GoldenGate
  • 16. 16 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Unique Fault Tolerance  Similar to storage mirroring  Duplicate in-memory columns on another node • Enabled per table/partition • Application transparent  Downtime eliminated by using duplicate after failure
  • 17. 17 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Implement in Minutes 1. Configure Memory Capacity  inmemory_size = XXX GB 2. Configure tables or partitions to be in memory  alter  table  |  partition    …    inmemory; 3. Drop analytic indexes to speed up OLTP
  • 18. 18 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Requires Zero Application Changes Full Functionality - No restrictions on SQL Easy to Implement - No migration of data Fully Compatible - All existing applications run unchanged Fully Multitenant - Oracle In-Memory is Cloud Ready Uniquely Achieves All In-Memory Benefits With No Application Changes
  • 19. 19 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Applications From Batch to Real-Time With In-Memory and Engineered Systems Oracle Database In-Memory Oracle Applications
  • 20. 20 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Real-Time Enterprise  Data Driven – Rapidly make decisions based on real-time data  Agile – Respond quickly to change  Efficient – Continually improve processes and profitability Real-Time Enterprise AGI LE EFFICIENT DATA- DRIVEN AGILE
  • 21. 21 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Cost Management  Adjust product mix, pricing, and marketing investments to maximize profits in real-time  Recalculate cost of every component in inventory, work-in-process, in-transit shipments, and finished good  Fast analysis of cost differences across manufacturing locations for make or buy decisions • 1.9 Billion Cost Rows • 13.8 Million Items • 14 Level BOM From 58 Hours to 13.5 Minutes 257X Faster
  • 22. 22 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. PeopleSoft In-Memory Financial Analyzer  Iterative financial position analysis in real-time  Make earlier decisions for the financial period  Speed account reconciliation  Shorten financial period close • 290M Ledger Lines • 250 Business Units • 7 Step Analysis, Pivot, Drill From 4.3 Hours to 11.5 Sec 1300X Faster
  • 23. 23 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Transportation Management  Dispatchers perform real-time monitoring and rerouting when en-route exceptions occur  Benefits of instant rerouting:  Reduction in empty miles and in Driver turnaround time  Improved on-time delivery  Improved Dispatcher efficiency and Driver retention • 145M Status Records • 60M Shipment Data Records • 16K Drivers From 16 Min to Sub-second 1030X Faster
  • 24. 24 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. JD Edwards Sales Order Analysis  Operational Analysis of sales orders in real-time  Find immediate answers to unanticipated customer sales questions  Eliminate batch jobs, data exports, third-party systems  1000’s  of  use  cases  across  all   functional areas • 104 million sales order lines From 22.5 Min to Sub-second 1700X Faster
  • 25. 25 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. JD Edwards Customer Receivables Management  Real-Time receivables summarization  Balances by customer, line of business, and currency  Eliminate multiple queries, batch jobs, data exports  Similar use cases for projects, suppliers, assets, inventory etc. • 10 million invoice lines From 244 Min to 4 Secs 3500X Faster
  • 26. 26 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Demantra Promotion Planning  Marketing Managers want detailed data when analyzing promotion plans  Benefits of real-time promotion analytics:  Analyze promotion profit and revenue on real-time basis  Optimize promotion spend  Better assess timing and cost impacts • 1.3 Billion Rows • Aggregate 36M rows • 2 week major sell-through report From 1120 to 11 Seconds 102X Faster
  • 27. 27 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Demantra Consumption Driven Planning  Daily store-level forecasting and replenishment requires processing high volume POS data multiple times a day  Benefits of real-time planning:  Consumption and shipment based forecasting in a single scalable system  Improved forecast accuracy and customer service levels at lower cost • 400 Million Rows • 1.4 Million SKU Locations From 12.7 Hours to 56 Minutes 13.5X Faster
  • 28. 28 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Supply Chain Planning and Analytics  Supply Chain analysts spend hours processing granular supply and demand data  Benefits of real-time planning:  Planners share business metrics with analysts  and  VP’s  of  Supply  Chain  real- time  Quickly solve supply disruptions and unexpected demand fluctuations • 360K Items • 1.2M Demands, 1M exceptions • 5.7M KPI records From 230 to 3 minutes 76X Faster
  • 29. 29 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Siebel Marketing – List Import  Real-time marketing for large numbers of prospects  Rapid processing of marketing data for campaign launch  Accelerate import of large numbers of prospects  Reduce data-cleansing time From 1.9 hours to 49 sec • Import and Cleanse 1 Million Records 140X Faster
  • 30. 30 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Fusion Cloud Financials Subledger Period Close Exceptions  Lists all accounting events and journal entries that fail period close validation in real-time  Report is run many times at end of quarter and is a bottleneck to close From 10 Minutes to 3 Sec • 19 Million Ledger Lines 210X Faster
  • 31. 31 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Fusion Cloud Financials Sales Pipeline Analytic Report • Report potential income in real-time • Aggregate revenue from opportunities grouped within each sales stage for a specific time period From 52 Minutes to 24 Sec • 1.6 million opportunities • 5.1 million revenue lines 129X Faster
  • 32. 32 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Become a Real-Time Enterprise Using Oracle Database In-Memory Real-Time Enterprise  Data-Driven • Get immediate answers to any question with real-time analytics  Agile • Eliminate latency with analytics directly on OLTP data  Efficient • Non-disruptively accelerate all applications AGI LE EFFICIENT DATA- DRIVEN AGILE
  • 33. 33 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Summary: Oracle Database In-Memory  Extreme Performance: Analytics & OLTP  Extreme Scale-Out & Scale-Up  Extreme Availability  Extreme Simplicity Powering the Real-Time Enterprise All In-Memory Benefits With No Application Changes
  • 34. 34 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.