Download Preview of Oracle Database 12c In-Memory Option

Preview of
Oracle Database 12c
In-Memory Option
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Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
The following is intended to outline our general product direction. It is
intended for information purposes only, and may not be incorporated
into any contract. It is not a commitment to deliver any material, code,
or functionality, and should not be relied upon in making purchasing
decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole
discretion of Oracle.
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Oracle Database In-Memory Option Goals
100X Faster Queries: Real-Time Analytics
 Get instantaneous query results
 Querying OLTP database or data warehouse
2X Faster Transaction Processing
Trivial to Deploy for All Applications and Customers
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Optimizing Transaction and Query Performance
Row Format Databases versus Column Format Databases
SALES
 Transactions run faster on row format
ORDER
Row
– Fast for processing few rows, many columns
– Example: Insert or query a sales order
SALES
Column
S
T
A
T
E
 Analytics run faster on column format
– Fast for processing few columns, many rows
– Example: Report on sales totals by state
Until Now You Choose One Format and Suffer Tradeoffs
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Breakthrough: Dual Format In-Memory Database
Memory
Memory
Sales
Row
Format
Sales
Column
Format
 BOTH row and column
in-memory formats for
same table
OLTP
 Simultaneously active and
Analytics
transactionally consistent
 Analytics & reporting use
New Column format
 OLTP uses row format
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Oracle In-Memory Columnar Technology
 Pure in-memory format with no logging
Memory
 Near zero overhead on changes
 Even for OLTP
 Uses memory-optimized compression
 2x to 10x memory reduction
Pure Columnar
 Data loaded in-memory for active tables
or partitions - on startup or first access
 For in-memory tables, >90% of memory
will be used for column format
 Row format needs little memory
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Find Any Business Data in Sub-second
Example: Find all sales in state of CA
• Each CPU scans local
in-memory columns
In-Memory Column Store
Sales
State column
>100X
Faster
 Scans use super fast
SIMD vector instructions
“CA”
scan rate per CPU core
CPU
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Load
multiple
State
values
SIMD
Compare
Compare all
all values
values in 1
in 1
cycle
instruction
Vector
Register
 Billions of rows/sec
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Scans and Combines Data from Multiple Tables
Example: Find all sales in outlet stores
Stores
 Converts join processing
into fast column scans
 Joins up to 10x faster
T
Y
P
E
Sales
Storeid
in
15,38,64
Type=outlet
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S
T
O
R
E
I
D
A
M
O
U
N
T
Sum
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Generate Reports In Sub-second
Example: Show sales trends for footwear
products in outlet stores
 Dynamically creates
in-memory report outline
Stores
Sales
 Report contents populated
In-Memory
Report Outline
during fact scan
 Reports up to 20x faster
without predefined cubes
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Products
Sales
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OLTP is Slowed Down by Analytic Indexes
 Most Indexes in mixed-use
OLTP (e.g. ERP) databases
are only used for analytics
Table
1 to 3
OLTP
Indexes
5 to 15
Analytics
Indexes
 Indexes work well for known
access patterns both
in-memory and on-disk
 But every change to the
table requires changing all
analytic indexes – Slow!
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Column Store Replaces Analytic Indexes
 In-Memory Column Store
replaces analytic indexes for
tables that fit in memory
Table
1 to 3
OLTP
Indexes
In-Memory
Column Store
 Removes analytic index
overhead on changes
 Both predefined and ad-hoc
analytic queries run fast
 Less tuning & admin needed
 OLTP & batch often run 2x or
more faster
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Demonstration at Oracle Openworld 2013
Performance of
columnar scan
vs. row scan
- Both in memory
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Extreme Capacity and Cost Effectiveness
 Size not limited by memory
DRAM
Hottest Data
PCI
FLASH
Active Data
 Data transparently
accessible across tiers
 Each tier has specialized
algorithms & compression
Capacity of Disk
IOs
of Flash
Speed of DRAM
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DISK
Cold Data
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Scale-Out In-Memory Database to Any Size
 Scale-Out across servers to
In Memory
Column Store
In Memory
Column Store
grow memory and CPUs
 In-Memory queries are
parallelized across servers to
access local column data
In Memory
Column Store
In Memory
Column Store
 Direct-to-wire InfiniBand
protocol speeds messaging
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Scale-Up for Maximum In-Memory Performance
 Scale-Up on large SMPs
 SMP scaling removes
overhead of distributing
queries across servers or
coordinating transactions
 Inter-processor bandwidth
far exceeds any network
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Oracle In-Memory is Trivial to Deploy
1. Configure Memory Capacity
 inmemory_area = XXXX GB
2. Configure tables or partitions to be in memory
 alter table | partition … inmemory;
3. Later Drop analytic indexes to speed up OLTP
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Oracle In-Memory is Transparent to Applications
Existing Applications Just Run Faster
Full Functionality
Trivial to Implement
Fully Compatible
DB as a Service Ready
- No restrictions on SQL
- No migration of data or change of product
- All existing applications run unchanged
- Oracle Multitenant in-memory
And All Other
Apps that Support
Oracle Database
Uniquely Achieves All In-Memory Benefits With No Application Changes
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Oracle In-Memory Delivers Extreme Availability
Data Guard & GoldenGate
 Pure In-Memory format does not
change Oracle’s storage format,
logging, backup, recovery, etc.
 All Oracle’s mature availability
RAC
technologies work transparently
 Protection from all failures
ASM
 Node, site, corruption,
human error, change, etc.
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RMAN
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Summary: Oracle Database In-Memory Option
• 100X Faster Queries: Real-Time Analytics
 Querying OLTP database or data warehouse
• 2X Increase Transaction Processing Rates
• Less Management and Tuning
• Best of Memory, Flash, Disk
• Scale-Out and Scale-Up
• Extreme Availability
Trivial to Deploy for All Applications and Customers
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APPENDIX
Relation of Database In-Memory Option
to TimesTen and Exadata
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Oracle Database In-Memory Products
TimesTen In-Memory Database
Oracle Database In-Memory
 Embedded in custom applications
 Extreme low latency OLTP workloads
(Microsecond Response Time)
 Adaptive In-Memory Cache for Exalytics
In-Memory Machine
 Scalable In-Memory Database for any type
of application workload
 Combines best of DRAM, flash, disk
Application
Application
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Application
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TimesTen In-Memory Database and Columnar
TimesTen Grid
 TimesTen is adding scale-out capabilities
– For both OLTP and analytics
 TimesTen is adding columnar technologies to
accelerate Analytics
Scale-Out In-Memory DB
– Core columnar processing engine is shared
between Oracle and Timesten
– Embedded Analytics engine
Columnar
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Oracle Database In-Memory Option on Exadata
• Exadata extends fast analytics from in-memory to flash and disk for highest
capacity and lowest cost
• Scale-out intelligent flash optimized storage: >100GB/sec from flash
• Exadata DB as a Service In-Memory delivers consolidation, ultra fast
performance, best agility, and lowest cost
• Highest performance applications run in-memory
• Applications that perform well today use cost-effective disk and flash
• Expect special optimizations for Database In-Memory on Exadata
• E.g. Fastest communication with InfiniBand Direct to Wire protocol
• Exadata is a standardized, pre-configured, pre-tuned, pre-tested platform for
database in memory, on flash, and on disk
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Platform of the Future
 Platform Engineered for Database
 Database Engineered for Cloud and
Consolidation
Enterprise
DBaaS
 Optimized for latest technologies
 In-Memory Database
 PCI Flash for fastest IO
 Disk for highest capacity
 Optimal compression at every tier
 Fastest Communication
 For all workloads – running together
 Highest performance, lowest cost,
most available, most scalable
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Confidential – Oracle Internal
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Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
Confidential – Oracle Internal