Ami Gal, Co-Founder & CEOon-demand.gputechconf.com/gtc/2014/presentations/S4749... ·...

Ami Gal, Co-Founder & CEO

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Analy&cs Performance -‐ 3 TB, 18 Billion records

SQream Technologies Ltd -‐ Confiden&al

#1 DB on #1 Server SQream on Dell R720

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Same Run5me Performance x400 Cost Performance

SQream DB the fastest “No-‐hassle” Big Data Analy5cs Database

Best Cost-‐Performance: Analyzing up to 100TB on an industry standard 2U server

Big Data Market forecast

4 SQream Technologies Ltd -‐ Confiden&al

40%-‐60% Service / Hassle

•  IBM, Oracle, SAP, HP, EMC, Teradata All new Hadoop -‐ SQL Startups

Compe&&ve Landscape of Big Data Insights


•  Established – 9/2010

•  28 fantas&c people

•  6 patent submissions

•  Focusing on –  Go-‐to market –  Product Scale

DNA of the company, partners and customers

Company Status


Nvidia GPUs advantages in a nutshell

•  Massive parallel compu&ng power

•  Aggressive data crunching

•  Extreme scalability

•  Low power consump&on


Use Case – Telco Revenue Assurance

•  Use case –  Handle Telco volume –  Run queries

•  Full scan aggrega&on -‐ Opera&onal

•  Join – Pre-‐Billing process –  Cost performance

•  SQream vs. Leading RDBMS –  Test performance

Load Time 300 Million CDRs

SQream Technologies Ltd -‐ Confiden&al 10

9

60

0

10

20

30

40

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60

70

Time in m

inutes

Load &me

Query Run Time 300 Million


0.015 195 10 60

10820

420

0

2000

4000

6000

8000

10000

12000

Count Query Join Query Aggrega&on Query

SQream vs. leading dbms -‐ Query Run Time 300 million

SQream Load Time


27

135

271

542

813

948

-‐200

0

200

400

600

800

1000

1 Billion 5 Billion 10 Billion 20 Billion 30 Billion 35 Billion

Time in m

inutes

# of CDR's in the table

Load &me

SQream Run Time – Select Count


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1 Billion 5 Billion 10 Billion 20 Billion 30 Billion 35 Billion

Select count

Benchmark SQream vs. leading DBMS

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SQream vs. leading DW – 1,000,000,000 CDRs


0

500

1000

1500

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2500

Q2 Q2 Q2 Q2 Q2 Q2 AVG

Second

s

•  Data Crunching: – Faster compression &me x20 – Faster decompression &me x50-‐x70 – Higher compression ra&o x5-‐x15

•  Compute: – Faster MPP in a node x20 – Higher scalability x1 node x3000 cores – Lower hardware cost $7,000,000 > $20K

Why SQream? Technology.


•  TCO – Lower power consump&on 1 node vs. 10 nodes – Lower storage and license cost x10 – x50 – Lower footprint 2U vs. 20U-‐42U

•  Deployment advantages – No indexes, no cubicles, no projec&ons. –  Built-‐in full scan ad-‐hoc queries support. – No code changes. Simple SQL.

Why SQream? Hassle free Solu&on.


Partners


Coming up customer engagements


SQream the fastest analy5cs ever Thank you!

See SQream and Orange today at 15:00, Room 210B

GeZng Bigdata done with GPUs Ori Netzer, SQream

Soumik Sinharoy, Orange

Ami Gal, Co-Founder & CEOon-demand.gputechconf.com/gtc/2014/presentations/S4749... ·...

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