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Lightning Talk MongoDB Boston, 10/1/14

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Agenda

•Introduction to Pure Storage and the All-flash (Storage) Array

•Infrastructure Considerations for MongoDB

•Recommendations

•Contact Info• Craig Halliwell, Emerging Alliances, ch@purestorage.com

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Introducing Pure Storage

Mission: Enabling the all-flash enterprise

Team: A team of 600+ storage industry veterans globally

Backing: $470M from committed investors

Differentiated Technology: 300+ patents in process

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Pure Storage is Flash for the Enterprise

Consistent performance100% MLC Flash

Less cost than diskInline deduplication & compression

Mission-critical reliability99.999%, non-disruptive operations

Scalable & compatible10 100s of TBs, Purity software

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Pure Storage FlashArray 400 Series

FA-405 FA-450FA-420

Up to 40TBs2 controllers in

2U

Up to 250TBs16 Gb/s FC

Up to 125 TBs

Licensing includes deduplication, snapshots, replication

Usable Capacity includes overheads for RAID-3D, Flash Management, GB-to-GiB conversion, and assumes 6-to-1 data reduction.

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Pure Storage “FlashReduce” Data Reduction

• Comprehensive, high-performance data reduction

• Pattern Removal • Adaptive, Inline Deduplication • Adaptive, Inline Compression • Deep Reduction • Zero-cost snapshots, clones & XCopy

• 5 – 10x reduction across broad number of data sets

• Reduces usable $/GB

* Based on CloudAssist data of Pure FlashArray deployments as of April 2014

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The Flash Price Barrier Has Been Broken!

$/GBHA

USABLEW/ SW

2012 2013 2014 2015 2016 2017…

$6$5 $4 10/15K

HDD

$2 $1.5 $1 SATAHDD

>$20

$15

$10

$6

$3

FlashAppliances

$8

$5

$4

$2$1

5-10xData Reduction!

Consumer SSD + Data Reduction

= Cost Parity to Disk

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Databases on Pure Storage – Endless Opportunities

Database

> 129%

QoQ

Q3 2013 Q4 2014

Database workloads account for over 60% of Pure Storage’s revenue…

…And growth is accelerating quarter over quarter.

Customers have achieved amazing results by running their database workloads on Pure

And they are loving it.

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Comparing Flash Approaches for Databases

100% Host PCIe Flash

Flash / Disk Caching(PCIe flash or

tiering arrays)All-flash Array

•Fastest performance for small (<500GB) databases

•Cost-effective for single application

•Breaks enterprise HA model•Requires re-architecture•Uses host CPU for flash

mgmt

•Can be added to existing infrastructure with minimal change

•Can apply to multiple servers

•Relies on cache hit rate•Latency introduced by

network•Ultimately limited by the

performance of disk• Inherits all the disk

inefficiencies

•Fully replaces existing storage

•Simple to manage•Suitable for many

applications•Always flash-fast with no

risk of caching/tiering•Dedicated CPU for dedupe,

compression, encryption•Latency introduced by

network

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Benefits of Shared Storage: Riding the CPU Curve

Separating CPU and Disk gives much better flexibility

• Compute / Storage innovations follow different cycles• Better investment protection as compute and storage can be

refreshed separately

Servers are becoming

DenserCheaper

CPU are becoming

FasterDenser

Cheaper

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MongoDB Scaling Recommendations

Compute Nodes

DB Size

1

2

4

8

1TB 2TB 4TB 8TB 16TB

Use Commodity Servers with PCIe Flash:

• Low node count • Low application

count• Small databases

Migrate to All-flash SAN when:

• Multiple nodes increase complexity

• Database size taxes disk I/O

Upgrade:• Servers based on

performance requirements and CPU cycles

• Storage based on capacity requirements

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Configuring Pure for MongoDB

• Provision a LUN of appropriate size for your DB• No need to create RAID groups• No need to set cache policies

• Pure is block storage, so access from compute nodes:• Via Ethernet for iSCSI• Via dedicated Fiber Channel Network

• Create DB clones via snapshot process in 7 UI-driven steps

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Pure Storage MongoDB Whitepaper

Step-by-step guide on - • Deploying MongoDB on Pure

Storage

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Case Study: Online Photo Company•Profile

• Rapid growth taxing traditional disk storage

•Performance• Move to Pure resulted in “Half the average response time”• 4x faster for replication to catch up after maintenance

•Efficiency:• Averaging 12 to 1 Data Reduction• 16TB Production Mongo Instance stored in 1.35TB of Pure Storage

•Simplicity• Array Installed in an hour• No configuration of devices • Mongo Team Manages Their Own Storage

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Can Pure Storage help me?

1. How big is your working set?

2. Are you living a life full of endless page faults?

3. Random workloads got your I/O spinning out of control?

4. Have you maxed out performance of your local SSDs?

5. How much space can you save by de-duping field names at the block level?

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Thank You! CONFIDENTIAL – DO NOT DISTRIBUTE