Storage Design for Datawarehousing

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Storage Subsystem Design for DatawarehousingArray, Drive and RAID Selection

Krishna Manoharan

[email protected]

http://dsstos.blogspot.com

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Again, what is this about?An attempt to show how to design a Storage Subsystem for an Datawarehouse Environment from a physical perspective.

Aimed at conventional environments using standard devices such as Fibre Channel SAN arrays for Oracle Databases.

The presentation will demonstrate the Array and Drive selection process using real life examples.

You will be in for a few surprises!

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Enterprise Business Intelligence (EBI)Most companies have multiple Oracle instances (such as ODS and DW) with an ETL Engine (Informatica) and Reporting tool (Business Objects) all rolled into an Enterprise Business Intelligence (EBI) Environment.

ODS is the Operational Data Store (a near real time copy of the company's Transactional data) and DW is the Datawarehouse (a collection of aggregated corporate data).

The ETL Engine (such as Informatica) transforms and loads data contained in the ODS into the DW.

The Reporting Engine (such as Business Objects) reports off data from both the ODS and DW.

This presentation covers the storage design for the DW.

Typical size of an DW is around 5-10TB for a large software company.

Though the typical Enterprise Warehouse is small in size, it is by no means less busy.

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Enterprise Business Intelligence (EBI) – contd.

Transaction Systems

DWODS

ETL Engine

Reports

Reporting Engine

OnlineSales

ClickStream

One Way Replication from Source Systems

Database Layer

Users

ERPHR CRM

Extract

Lo

ad

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Datawarehousing and the Storage Subsystem

One of the biggest factors affecting performance in Datawarehousing is the Storage subsystem.

Once the environment is live, it becomes difficult to change a storage subsystem or the layers within.

So it is important to design, size and configure the Storage subsystem appropriately for any Datawarehousing Environment.

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What is the Storage Subsystem?

System

CPU

Memory PCI

Switch

SAN Switch

Front End Ports to Host

Port 1 Port 2 Port n

CPU Cache

Array

SAN Fabric

Drives

The physical components of a conventional storage subsystem are

System PCI Interface

SAN Fabric

Array

In this presentation, we talk about the Array component of the Storage Subsystem.

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IO Fundamentals

IO in the simplest of terms is a combination of reads and writes.

Reads and Writes can be Random or Sequential.

READS are from the Storage

Subsystem

WRITES are to the Storage

Subsystem

Storage Subsystem

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IO Fundamentals – contd.Random or Sequential is determined at the array level (Meaningful)

Random Reads

Random Read Hit - If present in the Array Cache, then occurs at wire speed.

Random Read Miss - If not present in the Array Cache, hits the drives directly. This is the slowest IO operation.

Sequential Reads

First few reads are treated by the array as Random.

Judging by the incoming requests (if determined to be sequential), then data is pre-fetched from the drives in fixed sized chunks and stored in cache.

Subsequent reads are met from Cache at wire speed to the requestor.

Random/Sequential Writes

Normally are staged to cache and then written to disk.

Will occur at wire speeds to the requestor.

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IO MetricsKey IO Metrics are

IOPS – Number of IO requests/second issued by the application.

IO Size – The size of the IO requests as issued by the application.

Latency – The time taken to complete a single IO Operation (IOP).

Bandwidth – The anticipated bandwidth that the IO Operations are expected to consume.

Bandwidth is the total capacity of the pipe. Bandwidth capabilities are fixed.

DestinationSource

1024K264K

16K

264K

264K

1024K

16K

16K

16K

16K

Latency or response time is the time it takes for 1 IO Operation (IOP) to complete.

16K

16K

264K

16K

IOPS IOPS

264K 264K

16K 16K

1024K

16K

264K

16K

264K

1024K

16K

1024K

1024K

16K

16K

1024K

1024K

16K

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Datawarehousing Storage Challenges

Storage design in a corporate environment is typically Storage Centric - based on Capacity

Requirements, not Application Requirements. When applied to Datawarehousing, this

results in sub-standard user experience as Datawarehousing is heavily dependent on IO

performance.

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Profiling Datawarehousing IO - Reads

Reads

Users

From a IO performance perspective - Array capabilities along with Raid and Drive configuration determine Read performance in a Datawarehouse.

· Normally, in a conventional DW, you would notice many reports running against the same set of objects by different users for different requirements at the same time.

Object5

Object7

Object6

Object8

Object1

Object3

Object2

Object4

Object9

Objectn

Typical DW(less than 10TB)

· Since the size of the DW is not very big (~5-10TB) and hence the objects are relatively small in size, it is a normal tendency to place these objects on the same set of spindles (Also given the fact that today’s Drives are geared for capacity, not performance).

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· Due to high concurrency of the requests, about 60% of these read requests end up as Random Read Miss to the Array. Random Reads Miss is the slowest operation on an Array and require such reads to be met from the Disks.

· Such Random Reads can be big (1MB Sized IOP) or as small as DB Block Size. To accommodate both such requirements, throughput and latency require to be taken into consideration.

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· High degree of random concurrency (along with write intensive Loads) to single set of disks will absolutely kill your user experience.

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Da

tab

ase

O

bje

cts

Reads

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Profiling Datawarehousing IO – writesFrom a IO performance perspective, Cache sizing & Cache reservation along with Raid and Disk configurations determine write performance in a Datawarehouse.

· In a typical DW, different write operations occur at different intervals - 24*7*365.

· These writes can be direct path or conventional.

· Fast loading of data is important to be able to present the latest information to your customer. Normally, these are driven by rigid SLA’s.

Object5

Object7

Object6

Object8

Object1

Object3

Object2

Object4

Object9

Objectn

DW(Typically less than 10TB)

· In an Array environment, writes are staged to cache on the Array and then written to disks.

· Write performance would depend on the size of the cache and the speed at which data can be written to disks.

· If your cache overflows (Array not being able to keep up with the Writes), then you will see an immediate spike in write response times and corresponding impact on your write operation.

ETL EngineUsers (Temp Tablespace Writes)

Cache (Memory) on Array

· The speed at which data can be written to disks depends on the drive busyness.

· A combination of reads and writes occurring simultaneously to a single set of spindles will result in poor user experience.

· This normally happens when you place the objects on the same set of spindles without regard as to their usage patterns.

1

2

3Da

tab

ase

O

bje

cts

Writes

Writes

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Profiling Datawarehousing IO – Summary

To summarize (in Storage Terminology)

Enterprise Datawarehousing is an environment in which

Performance is important, not just capacity.

Read and Write intensive ( Typically 70:30 Ratio)

Small (KB) to large sized IOPS (> 1MB) – for both reads and writes.

Latency is very important and the IO Operations can consume significant amount of bandwidth.

In order to make these requirements more meaningful, you need to put numbers against each of these terms - for e.g. -IOPS, bandwidth and Latency - so that a solution can be designed to meet these requirements.

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Starting the Design

Okay I get the idea, so where do I begin?

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Storage Subsystem Design Process

If you have an existing Warehouse – Collect stats from all sources and correlate to ensure you are reading it correctly.

If not, then you would have to document your requirements based on an understanding of how your environment will be used and proceed to the design phase.

If not available, then document

requirements as best as you can.

Collect Stats from Oracle

Collect Stats from System

Collect Stats from Storage

Correlate Stats and Summarize/Forward

Project

Identify suitable Array

Drive

Identify suitable System(s)

Identify suitable SAN switches

Infrastructure Design

1 2 3

4

5

6 7

DriveRAID

Requirements Gathering Phase

If you have an existing Warehouse

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Storage Subsystem Design Requirements – contd.

If using the data from an existing Warehouse - Do a forward projection, using these stats as raw data, for your design requirements. The existing IO subsystem would be affecting the quality of the stats that you have gathered and you need to factor this in.

Separate out Reads and Writes along with the IO size.

Document your average and peak numbers at Oracle Level.

Anticipated IOPS – Number of IO Requests/Sec.

Anticipated IO Request Size – IO Request Sizes as issued by the application for different operations.

Acceptable Latency per IO Request.

Anticipated Bandwidth requirements as consumed by the IOPS.

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A Real World approach to the Design

In order to make the design process more realistic, let us look at

requirements for a DW for a large software company and use these requirements to build a suitable

Storage Subsystem.

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Requirements for a typical Corporate DW (Assuming 5TB in size)

PerformanceThe requirements below are as to be seen by Oracle. These are today’s requirements. It is expected that as the database grows, the performance requirements would scale accordingly.

Read peaks need not be at the same time as the Write peaks. Same scenario for multiblock/single block traffic.

Multi Block Reads Single Block Reads Multi Block Writes Single Block Writes

< = 30ms < = 10ms < 20ms < 5ms 5ms to 30ms

>16KB <= 1MB

(Average IOP Size 764K)16KB

>16KB <= 1MB

(Average IOP Size 512K)16KB 16KB to 1MB

Average 1200 IOPS 4000 IOPS 400 IOPS 450 IOPS 6050 IOPS

Peak 2000 IOPS 5200 IOPS 525 IOPS 650 IOPS 8375 IOPS

Average918 MB/sec

(Using 764K sized IOP)62.5 MB/sec

200MB/sec

(Using 512K sized IOP)7 MB/sec 1.2 GB/sec

Peak1492 MB/sec

(Using 764K sized IOP)81.2 MB/sec

262.5 MB/sec

(Using 512K sized IOP)10MB/sec 1.8 GB/sec

Bandwidth

Requirement TotalReads Writes

IOPS (IO Requests/Sec)

Acceptable Latency/IO

Request

Expected IO Request Size

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Requirements for a typical EDW (Assuming 5TB in size) – contd.

Capacity

The database is 5TB in size (Data/Index). And so provide 10TB of usable space on Day 1 to ensure that sufficient space is available for future growth (Filesystems at 50% capacity). Scale performance requirements appropriately for 10TB.

Misc

IO from redo/archive/backup is not included in the above requirements.

The storage subsystem needs to have the ability to handle 1024K IO Request size to prevent IO fragmentation.

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Conventional Storage thinking

Let us look at a typical Corporate Storage Design as a response to the

requirements.

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Requirements to Array & Drive Capabilities

The below would be a typical response to the requirements. However as we shall we, implementing as below would result in a failure.

Feature Requirement Recommended Notes

Net Bandwidth

Consumed

1.8 GB/sec (Today)

3.6 GB/sec (Tomorrow)

1 Hitachi Modular

Array AMS1000AMS1000 has 8*4Gb Front End Ports for a

total of 4 GB/sec Bandwidth

IOPS > 8375 IOPS

Latency 5ms to 30ms

Capacity 10TB

Max IO Size 1024K 1024K AMS1000 supports a 1024K IOP size.

CacheDetermines Writes

Performance16GB Maximum Cache is 16GB

Raid Levels - RAID10 RAID10 offers the best performance.

Stripe Width 1024K 512K512K is the maximum offered by the

array.

146GB, 15K RPM

Drives

165 Drives

10TB Usable (RAID

10)

Drive Specs of the 146GB, 15K RPM Drive

show that the requirements can be easily

met.

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Storage Subsystem Design Process - Array

What is required is a more thorough analysis of all the components of the storage

subsystem and then fit the requirements appropriately to the solution.

We start with the Array. This is the most vital part of the solution and is not easily

replaceable.

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Storage Array – Enterprise or Modular?

Arrays come in different configurations – Modular, Enterprise, JBOD etc.

Modular arrays are inexpensive and easy to manage. They provide good value for money.

Enterprise arrays are extremely expensive & offer a lot more functionality geared towards enterprise needs such as wan replication, virtualization and vertical growth capabilities.

As I will show later on, vertical scaling of an array is not really conducive for performance. Adding more modular arrays is a cheaper/flexible option.

For this presentation, I am using the Hitachi Modular Series AMS 1000 as an example.

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Typical Modular Array (simplified)

Conventional Array specs include

Number/Speed of Host Ports (Ports available for the host system to connect to).

Size of Cache.

Maximum Number of Drives.

Number of Raid Controllers.

Number of Backend Loops for Drive connectivity.

Disk Controllers


Raid Controllers

Drives

CacheManagement CPU

Port 1 Port xPort 2Array

SAN Switch

Servers

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Oracle requirements to Array Specs

Unfortunately Array specs as provided by the vendor do not allow us to match it with Oracle requirements (apart from Capacity). So you need to ask your Array vendor some

questions that are relevant to your requirement.

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Array Specs – contd. (Questions for Array Vendor)

Disk Controllers


Raid Controllers

Drives

CacheManagement CPU

Port 1 Port xPort 2

Array

· Are these ports full

speed?

· What is the queue

depth they can

sustain?

· Maximum IO Size that

the Port can accept?

What is the bandwidth

available between these

components?

· How may drives can

this array sustain

before consuming

the entire bandwidth

of the array?

· Optimal Raid

Configurations?

Can we manipulate the

Cache reservation policy

between Reads and

Writes?

How many CPUs in all?

1

2

3

4

5

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The HDS AMS1000 (Some questions answered)

Disk Controllers


2 Raid Controllers

Drives

CacheManagement CPU

Port 1 Port xPort 2

AMS1000

· Are these ports full speed? –

Only 4 out of 8 are Full Speed

for a peak speed of 2048MB/

sec.

· What is the queue depth they

can sustain? – 512/Port

· Maximum IO Size that the Port

can accept? – 1024K

What is the bandwidth

available between these

components? – Effective

Bandwidth is 1066 MB/sec

· How may drives can this array sustain before

consuming the entire bandwidth of the array?

– Depends on Drive Performance

· Optimal Raid Configurations? – Raid 1 or Raid

10. For Raid 5 – Not enough CPU/Cache.

· Raid 10 – Stripe width 64K default, Upto 512K

with CPM (License)

Can we manipulate the Cache

reservation policy between

Reads and Writes? - No

How many CPUs in all?

12.8 GB/sec

1066 MB/sec

2132 MB/sec

2048 MB/sec (Simplex)

2 C

PU

1 RAID

CPU/

Controlle

r

4 Tachyon

Chips

4 Tachyon

Chips

1

2

3

5

4

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Analyzing the HDS AMS1000

Regardless of internal capabilities, you cannot exceed 1066 MB/sec as net throughput (Reads and Writes).

Limited Cache (16GB) and the inability to manipulate cache reservation means that faster and smaller drives would be required to complete writes in time.

The 1066MB/sec limit and the Backend Architecture restricts the number of drives that can be sustained by this array.

Limited number of CPUs and Cache rule out using RAID 5 as a viable option.

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Matching the AMS1000 to our requirements

Feature RequirementAMS1000

Capability Recommendation Notes

Net Bandwidth

Consumed

1.8 GB/sec (Today)


1066MB/sec (Theoritical)

750 MB/sec (Realistic)

5 Arrays (Min)

8 Arrays (Recommended)

1 AMS1000 = 750MB/sec

5 AMS1000 = 3.6 GB/sec

8 AMS1000 = 5.8 GB/sec

IOPS > 8375 IOPS

Latency 5ms to 30ms

Capacity 10TB

Scalability Future growth

Max IO Size 1024K 1024K 1024K1024K is supported on the

AMS1000.


Performance16GB 16GB (Max)

Cache is preset at 50%

Reads/Writes

Raid Levels - RAID 0, RAID 1, RAID 10, RAID 5 RAID 1 and RAID 10 Not enough CPU for RAID 5

Stripe Width 1024K 64K, 256K and 512KTest to determine stripe

widthBeyond 64K, require

additional License feature

Need to simulate the

requirements along with

various drive and raid

configurations.

Depends on type of IO Operation, RAID/Drive

performance and Drive Capacity.

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HDS AMS1000 - Conclusions

Bandwidth requirements – We would need min of 5 Arrays to meet today + future requirement.

Physical hard drives and RAID configuration determine the storage capacity and other performance requirements (IOPS/Latency).

Testing various configurations of Drive and RAID levels would determine how desired requirements - (IOPS/latencies) can be met.

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Storage Subsystem Design Process – The Drives

Now that we have established Array capabilities, we can move

on to the Drive Selection.

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Hard Drives

Regardless of how capable your array is, the choice of the Drives will ultimately decide the performance.

Ultimately all IO gets passed down to the physical hard drives.

The performance characteristics (Throughput, IOPS and Latency) vary depending of the type of the IO request and the drive busyness.

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Hard Drives – FC or SATA or SAS

Choice limited by selection of array.

The drive interface speed (2Gb/4Gb etc) is not relevant as the bottleneck is the media and not in the interface.

SAS is a more robust protocol than FC with native support for dynamic failover.

SAS is a switched, serial and point to point architecture whereas FC is Arbitrated Loop at the Backend.

The IDE equivalent of SAS is SATA. SATA offers larger capacities at slower speeds.

For an Enterprise DW with stringent IO requirements, SAS would be the ideal choice (If Array supports SAS).

Faster the drives, better the overall performance.

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Hard Drives – Capacities – Is bigger better?

What Capacity should I pick?

Bigger drives results in the

ability to store more objects

resulting in more concurrent

requests and thus a more

busier drive.

All offer (supposedly) same performance

167 Random IOPS at 8K IO Size

73-125 MB/sec (Sustained)

Object1

Object3

Object2

Object4

Object1

Object3

Object2

Object4

Object5

Object7

Object6

Object8

Object1

Object3

Object2

Object4

Object5

Object7

Object6

Object8

Object1

Object3

Object2

Object4

Object5

Object7

Object6

Object8

146GB

300GB

450GB

But if you compare IOPS/GB, then the

true picture is revealed.

146GB drive = 1.14 IOPS/GB



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Performance of Drives vis-à-vis Active Surface Usage

As free space is consumed on the drive, so does the performance start to degrade. Smaller drives are a better choice for Enterprise Warehousing.

0

50

100

150

200

250

300

25% 50% 75% 100%

IOP

SR

and

om

8K

% Active Surface Usage

15K RPM Drive

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Hard Drives Specs

Hard Drive specs from Manufacturers typically include the below:

Capacity – 146GB, 300GB, 450GB etc

Speed – 7.2K/10K/15K RPM

Interface Type/Speed – SAS/FC/SATA, 2/3/4 Gb/sec

Internal Cache – 16MB

Average Latency – 2 ms

Sustained Transfer rate – 73-125 MB/sec

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Oracle requirements to Disk Specs

Unfortunately Disk specs as provided by the vendor do not allow us to match it with Oracle requirements (apart from Capacity). Also, Hard Drives are always used in a RAID Configuration (In an Array). So you need to test various RAID Configurations and arrive at conclusions that are relevant to your requirement.

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RAID, Raid Groups & LUNS

RAID GROUP 2

LUN 1

LUN 2

LUN 3

Systems

· Luns are carved out from Raid Groups on the Array.

· Raid Groups are sets of disks in the Array in pre-defined combinations (Raid 1, Raid 5, Raid 10 etc).

Host Systems see Luns as individual disks (presented by the Array).

Array

RAID GROUP 1

LUN 4

LUN 5

RAID is essentially a method

to improve drive performance by splitting requests between multiple drives and reduce drive busyness.

And provide redundancy at the same time.

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RAID Levels – RAID 1

Minimal CPU utilization during routine/recovery operations.

Not Cache intensive.

Since traditional RAID 1 is 1D+1P combination, it would require combining multiple such luns on the system to create big volumes.

Reads from either drive will help reduce drive

busyness.

Writes require 2 IOP (Overwrite existing data)

RAID 1MIRROR

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RAID Levels – RAID 5Each additional IO operation will consume bandwidth within the array.

Depending on stripe width, a request may be split between drives.

CPU Intensive due to parity bit calculation.

High Write Penalty and hence Cache intensive.

High CPU overhead during recovery.

Bigger the RAID group (More drives), higher the penalty (especially during recovery).

DATA1 DATA2 DATA3 PARITY

DATA4 DATA5 PARITY DATA6

RAID 5

Reads will be split across drives depending on size of IO request/stripe width and help

reduce drive busyness.

Writes require 4 IOP

(Retrieve Data & Parity into Cache, Update Data & Parity in Cache and then Write Back

into Disk)

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RAID Levels – RAID 10Combines both RAID1 and RAID0.

Same advantages of RAID1 with the advantage of striping (scaling across multiple drives).

With a bigger stripe width, the IO requests can be met within a single drive.

Traditionally Modular Arrays have been able to offer lengths of 64K stripe width only (on a single disk). This means that an IO request exceeding 64K would need to be split across the drives.

Splitting across drives means more IOP’s and consuming more backend capacity (overall Array+ Drive busyness).

Newer arrays (AMS2500) offer up to 512K stripe width.

You can do a combination of RAID1 on the array and stripe on the system (Volume Manager) to overcome the array stripe width limitation.

DATA1 DATA1

DATA2 DATA2

DATA3 DATA3

DATA4 DATA4

· Reads from either of the mirrored drives.

· Reads will be split across drives depending on size of IO request/stripe width.

MIRROR

MIRROR

MIRROR

MIRROR

Writes require 2 IOP (Overwrite existing data)

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Drive and RAID – Initial Conclusions

Since the AMS1000 supports only FC/SATA drives, we will use FC Drives.

We will test using 146GB 15K RPM drives.

RAID5 is not an option due to high write penalty.

RAID10 on the array is not an option as the array can offer only 512K stripe width. Our preference is 1024K stripe width so that a single 1024K multiblock IO request from Oracle can (at best) be met from a single drive.

This leaves us with only RAID1 on the array.

We can test using RAID1 and RAID10 (Striping on the system) under various conditions.

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RAID Level Performance Requirements

The intent is to identify individual drive performance (in a RAID configuration).

This will allow us to determine the number of drives that will be required to meet our requirements.

We will simulate peak reads/writes to identify a worst case scenario.

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Test Methodology to determine Drive performance

We will simulate Oracle traffic for 20 minutes using VxBench.

We will test on a subset (400GB) of the 5TB expected data volume.

We will generate the required IOPS and measure latency and consumed bandwidth.

Operations Type IO Size IOPS IOPS for 20 minutes

Multiblock IOP Asynchronous 784K 156 IOPS 187200

Single Block OP Sync 16K 406 IOPS 487200

Operations Type IO Size IOPS/sec IOPS for 20 minutes

Multiblock IOP Asynchronous 512K 41 IOPS 49200

Single Block OP Sync 16K 51 IOPS 61200

Reads

Writes

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And the results are ..RAID Config

Active Surface

Area /DriveData Drives Feature Expectation Actual Notes

IOPS 654 IOPS 567 IOPS

Bandwidth 147 MB/sec 141 MB/sec

Latency 5ms to 30 ms 46 ms










16

68% 8

68% 8

400 GB

RAID 1 4 Concat Volumes across

4 Raid 1 Luns

RAID 10 2 Stripe Volumes across 4

RAID 1 luns

(Raid 0 on system and

Raid 1 on Array)

RAID1 8 Concat Volumes across

8 Raid 1 Luns

RAID 10 4 Stripe Volumes across

8 RAID 1 luns

(Raid 0 on system and

Raid 1 on Array)

33% 16

400 GB

33%

Linux Host with

NOOP Elevator and

Vxvm Volumes.

Linux Host with

NOOP Elevator and

Vxvm Volumes (1MB

Stripe Width)

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Drive and RAID conclusions

RAID1 on a Linux Host outperforms a RAID10 combination (RAID0 + RAID1 Combination).

To meet our requirements, usable surface area cannot exceed 33% of a single 146 GB, 15K RPM FC Drive.

For 10 TB (Day 1 + Future growth), we would need 410 drives of 146GB, 15K RPM Drives.

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Match requirements to Array and Drive capabilities

Now that we have established both Array and Drive capabilities, we can

finally match these to our requirements.

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Requirements to Array & Drive Capabilities

Feature Requirement Typical Storage DesignActual Minimum

RequirementRecommended Notes

Net Bandwidth

Consumed

1.8 GB/sec (Today)


1 Hitachi Modular Array

AMS10005 AMS1000 Arrays

8 AMS1000 Arrays is

preferable.

1 AMS1000 = 750MB/sec

5 AMS1000 = 3.6 GB/sec

8 AMS1000 = 5.8 GB/sec

IOPS > 8375 IOPS

Latency 5ms to 30ms

Capacity 10TB

Max IO Size 1024K 1024KAMS1000 can meet the

required 1024K IOP Size.- -


Performance16GB 16GB - Maximum Cache is 16GB

Raid Levels - RAID10 RAID1 RAID1RAID1 (on a Linux system)

performed better than RAID10.

Stripe Width 1024K 512K NA - -

146GB, 15K RPM Drives

450 Drives (410 + 40)

90 Drives/Array

2TB/Array (Usable space)

410 Drives to meet Performance

and Capacity Requirements

450 drives (Including Spares)


450 Drives (410 + 40)

60 Drives/Array

1.3 TB/Array (Usable Space)


165 Drives

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Final Thoughts

If we had followed the capacity method of allocating storage to the Instance, a single AMS1000 would have been sufficient. But as we discovered, we would require at least 5 arrays to meet requirements.

Similarly, the initial recommendation was 165 146GB drives . However we determined that a minimum of 410 drives is required to meet performance requirements.

Out of the 146GB of available capacity in the drive, only 49GB is really usable.

RAID1 outperforming RAID10 is a surprise, but this may not be case on all platforms. The choice of Operating System, Volume Management and other configuration aspects do influence the final outcome.

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The Future is Bright

As always, Low Price does not equal Low Cost. If you design the environment appropriately, you will spend more initially, but the rewards are plentiful.

Modular Arrays are continuously improving and the new AMS2500 from Hitachi has an internal bandwidth capability of 8GB/sec (Simplex). So a single AMS2500 would suffice for our needs from a Bandwidth perspective.

Solid State Devices appears to be gaining momentum in the main stream market and hopefully within the next 2 years, HDD will be history.

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Questions ?

Storage Design for Datawarehousing

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