Snapfish, a web-based photo and printing service, will walk through their evaluation process for a new database, discuss use cases, and how they plan to use Scylla in their production systems.

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First and last name
Position, company
Quest for a Fast NoSQL DB
Principal Engineer, Snapfish
Brent Williams

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Position, company
BRENT WILLIAMS
2
I'm a Software Architect and I have spent the last 20
years of my career building out solutions for
Fortune 500 companies such as Amazon, HP,
Staples, NBC and more.
I am currently working at Snapfish developing
solutions to manage Storage at Scale.

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Position, company
ABOUT SNAPFISH
An industry leader in photo retail and creative prints
Over 100 million members operating across the globe
Over 40 billion images stored over the past 15 years

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Position, company
IN SEARCH FOR A FAST NOSQL DB
Current platform no longer ideal for scaling plans
Ideal platform excels in performance, stability, cost

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Position, company
IN SEARCH FOR A FAST NOSQL DB
Current DB operations on peak shopping day
o 100,000 read/min
o 7,000 write/min
Backend DB requirement for continuous image migrations
o 80,000 read/min
o 80,000 write/min

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PERFORMANCE CHECK
SMALL CLUSTER, INTERNAL HYPERVISOR
Target Machines
▪ 4 node cluster
▪ 4 cores
▪ 32 GB RAM
▪ 2 TB SAN Storage
▪ ScyllaDB v.1.7
Test Runners
▪ 5 node cluster
▪ 4 cores
▪ 16 GB RAM
▪ Java 8
▪ DataStax 3.3 with
stress tester
Stress Test
▪ Heavy Inserts
▪ Heavy Reads and
Updates
▪ CRUD
▪ CRUD with heavy
migration load

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Position, company
PERFORMANCE CHECK
SMALL CLUSTER, INTERNAL HYPERVISOR
Disk Writes
per server per second
Disk Writes
Bps per server
Disk Reads
Bps per server
Disk Reads
per server per second
200 iops
20 MBps
3000 iops
10 MBps
CPU load maxed

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LARGE CLUSTER PERFORMANCE
AMAZON WEB SERVICES
Results
Test Parameters
• 160 total threads
• 30 minutes per test
Test 1
Create + Read
Test 2
Read + Update
Test 3
CRUD
Creates 20.9M NA 21M
Reads 101.5k 152.7k 100.5k
Updates NA 5.5M 5.3M
Deletes NA NA 43.4k
Avg Ops/Sec 11.K 3.1k 14.6k
Test Runners
▪ 5 node cluster
▪ 4 cores
▪ 16 GB RAM
▪ Java 8
▪ DataStax 3.3 with
stress tester
Target Machines
▪ 3 node cluster
▪ 16 cores
▪ 122 GB RAM
▪ 2 TB SSD
▪ ScyllaDB v.1.7

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Position, company
Future Scale
Current platform no longer ideal for scaling plans

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Position, company
Selection Criteria
Resolves constraints at the most
appropriate layer while still
maintaining
all functions we require in a DB.
Functional
Vendor Stability
Economics
Performance
✓

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Selection Criteria
Scylla DB is fast, 5x faster
than our current set up.
Functional
Vendor Stability
Economics
Performance✓
✓

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Selection Criteria
Licensing is far less than
current technology without the
need for costly upgrades.
Functional
Vendor Stability
Economics
Performance
✓
✓
✓

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Position, company
Selection Criteria
Company has eyes on the
right problems to solve for in
today’s challenge of scale.
Functional
Vendor Stability
Economics
Performance
✓
✓
✓
✓

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VERDICT
ScyllaDB just may be
the world’s fastest NoSQL Database!
Functional
Vendor Stability
Economics
Performance
✓
✓
✓
✓

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THANK YOU
www.snapfish.com
Please stay in touch
Any questions?