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Copyright © 2013, Oracle and/or its affiliates. All rights reserved.1
Preview of Oracle Database 12c In-Memory Option
Thomas Kytehttp://asktom.oracle.com/
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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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Flip Flops
Core
ICs on board
DIMMS
SIMMs
SSD
Flash
Small Drives
Floppy
Big Drives
1993 ~$25/mb; $26,214,400/tb
2014 ~$0.007/mb; $7,645/tb
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Oracle Database In-Memory Option Goals
100X Faster Queries: Real-Time AnalyticsGet instantaneous query resultsQuerying OLTP database or data warehouse
Faster Transaction Processing
Trivial to Deploy for All Applications and Customers
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Until Now You Choose One Format and Suffer Tradeoffs
Optimizing Transaction and Query Performance Row Format Databases versus Column Format Databases
Row
Transactions run faster on row format– Fast for processing few rows, many columns– Example: Insert or query a sales order
Column
Analytics run faster on column format– Fast for processing few columns, many rows
– Example: Report on sales totals by state
ORDER
SALES
SALES
STATE
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BOTH row and column in-memory formats forsame table
Simultaneously active and transactionally consistent
Analytics & reporting use New Column format
OLTP uses row format
BOTH row and column in-memory formats forsame table
Simultaneously active and transactionally consistent
Analytics & reporting use New Column format
OLTP uses row format
Breakthrough: Dual Format In-Memory Database
Column Format
Memory
Row Format
Memory
AnalyticsOLTP Sales Sales
Sales
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Oracle In-Memory Columnar Technology
Memory
Pure Columnar
Pure in-memory format with no logging
Near zero overhead on changes Even for OLTP
Uses memory-optimized compression 2x to 10x memory reduction
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
Pure in-memory format with no logging
Near zero overhead on changes Even for OLTP
Uses memory-optimized compression 2x to 10x memory reduction
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
SIMD Compare all values in 1 cycle
Compare all values
in 1 instruction
Load multiple State
values Vec
tor
Reg
iste
r
In-Memory Column Store
State columnSales
Example: Find all sales in state of CA
“CA”
>100X Faster
• Each CPU scans local in-memory columns
Scans use super fast SIMD vector instructions
Billions of rows/sec scan rate per CPU core
• Each CPU scans local in-memory columns
Scans use super fast SIMD vector instructions
Billions of rows/sec scan rate per CPU core
CPU
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Scans and Combines Data from Multiple Tables
SalesStores
Type=outlet
Example: Find all sales in outlet stores
TYPE
Storeid in
15,38,64
STOREID
AMOUNT
Converts join processing into fast column scans
Joins up to 10x faster
Converts join processing into fast column scans
Joins up to 10x faster
Sum
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OLTP is Slowed Down by Analytic Indexes
Table1 to 3OLTP
Indexes
5 to 15 AnalyticsIndexes
Most Indexes in mixed-use OLTP (e.g. ERP) databases are only used for analytics
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!
Most Indexes in mixed-use OLTP (e.g. ERP) databases are only used for analytics
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
Table1 to 3OLTP
Indexes
In-Memory Column Store replaces analytic indexes for tables that fit in memory
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
In-Memory Column Store replaces analytic indexes for tables that fit in memory
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
In-Memory Column Store
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Extreme Capacity and Cost Effectiveness
Size not limited by memory
Data transparently accessible across tiers
Each tier has specialized algorithms & compression
Capacity of Disk IOs of Flash Speed of DRAM
Size not limited by memory
Data transparently accessible across tiers
Each tier has specialized algorithms & compression
Capacity of Disk IOs of Flash Speed of DRAM DISK
PCI FLASH
DRAM
Cold Data
Hottest Data
Active Data
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Scale-Out In-Memory Database to Any Size
Scale-Out across servers to grow memory and CPUs
In-Memory queries are parallelized across servers to access local column data
Direct-to-wire InfiniBand protocol speeds messaging
Scale-Out across servers to grow memory and CPUs
In-Memory queries are parallelized across servers to access local column data
Direct-to-wire InfiniBand protocol speeds messaging
In MemoryColumn Store
In MemoryColumn StoreIn Memory
Column Store
In MemoryColumn Store
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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
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_size = 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 ApplicationsExisting Applications Just Run Faster
Full Functionality - No restrictions on SQL
Trivial to Implement - No migration of data or change of product
Fully Compatible - All existing applications run unchanged
DB as a Service Ready - Oracle Multitenant in-memory
Uniquely Achieves All In-Memory Benefits With No Application Changes
And All Other Apps that Support Oracle Database
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Oracle In-Memory Delivers 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, change, etc.
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, change, etc.
RAC
ASM
RMAN
Data Guard & GoldenGate
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• Faster Queries: Real-Time Analytics Querying OLTP database or data warehouse
• 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
Summary: Oracle Database In-Memory Option
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