preview of oracle database 12c in-memory option · title: slide 1 author: juan loaiza subject:...
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Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 1
Preview of Oracle Database 12c In-Memory Option
Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 2
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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3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
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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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
S
T
A
T
E
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BOTH row and column
in-memory formats for
same 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
Analytics OLTP 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
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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 Vecto
r
Reg
iste
r
In-Memory Column Store
State column Sales
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 CPU
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Scans and Combines Data from Multiple Tables
Sales Stores
Type=outlet
Example: Find all sales in outlet stores
T
Y
P
E
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 up to 10x faster
Sum
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Generate Reports In Sub-second
In-Memory
Report Outline
Example: Show sales trends for footwear products in outlet stores
Stores
Products
Sales
Sales
Dynamically creates
in-memory report outline
Report contents populated
during fact scan
Reports up to 20x faster
without predefined cubes
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OLTP is Slowed Down by Analytic Indexes
Table 1 to 3
OLTP
Indexes
5 to 15
Analytics
Indexes 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
Table 1 to 3
OLTP
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
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Demonstration at Oracle Openworld 2013
12
Performance of
columnar scan
vs. row scan
- Both in memory
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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 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
In Memory
Column Store
In Memory
Column Store In Memory
Column Store
In Memory
Column 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
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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 - 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.
RAC
ASM
RMAN
Data Guard & GoldenGate
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• 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
Summary: Oracle Database In-Memory Option
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APPENDIX
Relation of Database In-Memory Option to TimesTen and Exadata
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Oracle Database In-Memory Products
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Application
Application
Application
TimesTen In-Memory Database
Embedded in custom applications
Extreme low latency OLTP workloads
(Microsecond Response Time)
Adaptive In-Memory Cache for Exalytics
In-Memory Machine
Oracle Database In-Memory
Scalable In-Memory Database for any type
of application workload
Combines best of DRAM, flash, disk
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TimesTen In-Memory Database and Columnar
TimesTen is adding scale-out capabilities
– For both OLTP and analytics
TimesTen is adding columnar technologies to
accelerate Analytics
– Core columnar processing engine is shared
between Oracle and Timesten
– Embedded Analytics engine
TimesTen Grid
Scale-Out In-Memory DB
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
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
Enterprise
DBaaS
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