Big data poses big challenges for accessing and analyzing information. BLU Acceleration from IBM delivers speed of thought analytics that help you make better decisions faster. See BLU Acceleration’s innovative dynamic in-memory processing, actionable compression, parallel vector processing and data skipping. Learn how to get started using your existing infrastructure and skills.
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“We have for the first time an economy
based on a key resource [Information] that
is not only renewable, but self-generating.
Running out of it is not a problem,
but drowning in it is.”
- John Naisbitt, Author and Futurist
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To stay ahead of this big data
explosion, we need to:
4. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Analyze more data, faster
To stay ahead of this big data
explosion, we need to:
5. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Analyze more data, faster
Simplify set up and use
To stay ahead of this big data
explosion, we need to:
6. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Analyze more data, faster
Simplify set up and use
Support existing systems
To stay ahead of this big data
explosion, we need to:
7. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Analyze more data, faster
Simplify set up and use
Support existing systems
Use existing skills
To stay ahead of this big data
explosion, we need to:
8. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Analyze more data, faster
Simplify set up and use
Support existing systems
Use existing skills
Eliminate need for code changes
To stay ahead of this big data
explosion, we need to:
9. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
In other words, make it
super fast and super easy
to access and analyze big data.
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Introducing BLU Acceleration from IBM:
A new generation of data management
innovation capable of delivering
speed of thought analytics.
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Testing of BLU Acceleration shows:*
*Based on internal IBM testing of sample analytic workloads comparing queries accessing row-based tables on
DB2 10.1 vs. columnar tables on DB2 10.5. Performance improvement figures are cumulative of all queries in
the workload. Individual results will vary depending on individual workloads, configurations and conditions.
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Faster reporting
and analytics
258times
Testing of BLU Acceleration shows:*
*Based on internal IBM testing of sample analytic workloads comparing queries accessing row-based tables on
DB2 10.1 vs. columnar tables on DB2 10.5. Performance improvement figures are cumulative of all queries in
the workload. Individual results will vary depending on individual workloads, configurations and conditions.
13. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Faster reporting
and analytics
258times
Storage space
savings
01times
Testing of BLU Acceleration shows:*
*Based on internal IBM testing of sample analytic workloads comparing queries accessing row-based tables on
DB2 10.1 vs. columnar tables on DB2 10.5. Performance improvement figures are cumulative of all queries in
the workload. Individual results will vary depending on individual workloads, configurations and conditions.
14. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
“We were very impressed with the
performance and simplicity of BLU.
We found that some queries
achieved an almost 100x speed
up with literally no tuning!”
- Lennart Henäng, IT Architect, Handelsbanken
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BLU Acceleration achieves
top performance efficiency with:
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Dynamic In-Memory
In-memory columnar processing with
dynamic movement of data from storage
BLU Acceleration achieves
top performance efficiency with:
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Dynamic In-Memory
Actionable Compression
Patented compression technique that
preserves order so data can be evaluated
BLU Acceleration achieves
top performance efficiency with:
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Dynamic In-Memory
Actionable Compression
Parallel Vector Processing
Multi-core and SIMD parallelism
(Single Instruction Multiple Data)
BLU Acceleration achieves
top performance efficiency with:
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Dynamic In-Memory
Actionable Compression
Parallel Vector Processing
Data Skipping
Skips processing of irrelevant data
BLU Acceleration achieves
top performance efficiency with:
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With these innovations,
BLU Acceleration can perform
queries at the speed of thought…
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Actionable Compression
reduces to 1TB
In-memory
DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Actionable Compression
reduces to 1TB
In-memory
Column Processing
reduces to 10GB
DATA DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Actionable Compression
reduces to 1TB
In-memory
Column Processing
reduces to 10GB
Data Skipping
reduces to 1GB
DATA DATA DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Actionable Compression
reduces to 1TB
In-memory
Parallel Processing
32MB linear scan
on each core via
Column Processing
reduces to 10GB
Data Skipping
reduces to 1GB
DATA DATA DATA
DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Actionable Compression
reduces to 1TB
In-memory
Parallel Processing
32MB linear scan
on each core via
Vector Processing
Scans as fast as
8MB through SIMD
Column Processing
reduces to 10GB
Data Skipping
reduces to 1GB
DATA DATA DATA
DATA DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Actionable Compression
reduces to 1TB
In-memory
Parallel Processing
32MB linear scan
on each core via
Vector Processing
Scans as fast as
8MB through SIMD
Answers at the
speed of thought
Column Processing
reduces to 10GB
Data Skipping
reduces to 1GB
DATA DATA DATA
DATA
DATA DATA
10TB Data
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
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Getting started with
BLU Acceleration is also
super fast and super easy...
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1. Decide on partition strategies
2. Select Compression Strategy
3. Create Table
4. Load data
5. Create Auxiliary Performance
Structures
A. Materialized views
B. Create indexes
a. B+ indexes
b. Bitmap indexes
6. Tune memory
7. Tune I/O
8. Add Optimizer hints
9. Statistics collection
Repeat
Database Design
and Tuning
30. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
1. Decide on partition strategies
2. Select Compression Strategy
3. Create Table
4. Load data
5. Create Auxiliary Performance
Structures
A. Materialized views
B. Create indexes
a. B+ indexes
b. Bitmap indexes
6. Tune memory
7. Tune I/O
8. Add Optimizer hints
9. Statistics collection
Repeat
vsDatabase Design
and Tuning
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Database Design
and Tuning
BLU Acceleration
1. Decide on partition strategies
2. Select Compression Strategy
3. Create Table
4. Load data
5. Create Auxiliary Performance
Structures
A. Materialized views
B. Create indexes
a. B+ indexes
b. Bitmap indexes
6. Tune memory
7. Tune I/O
8. Add Optimizer hints
9. Statistics collection
Repeat
1. Create Table
2. Load data
vs
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BLU Acceleration
No Indexes,
No Aggregates,
No Tuning,
No SQL changes,
No schema changes
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Faster set-up and faster performance
means faster insights from more data...
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Enabling you to use big data to make
better decisions, better serve your
customers, improve the efficiency of
operations and reduce risk.
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Built into DB2 10.5
BLU Acceleration:
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Built into DB2 10.5
Doesn’t require
specific configurations
BLU Acceleration:
38. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Built into DB2 10.5
Doesn’t require
specific configurations
Extends and enhances
value of existing investments
BLU Acceleration:
39. Put BLU Acceleration to work: IBMbigdatahub.com/IBMBLU
Built into DB2 10.5
Doesn’t require
specific configurations
Extends and enhances
value of existing investments
Flexible deployment
BLU Acceleration: