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building lightning fast appsover CF and BOSH

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Leading the commercial Redis market

Founded in 2011; GA in 02/2013

2,200+ paying customers; 50,000+ DBs; 100+

new DBs/day

2nd largest contributor to open source Redis

Raised $13M - Bain/Carmel/Strategic/Angels

Offices in Santa Clara and Tel-Aviv

In a nutshell

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Redis Cloud Memcached Cloud

Our offering

Fully-managed cloud services.

On-prem server license - soon.

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Launching Redis Labs

Clusterwith BOSH

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Why Redis ?

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The newest NoSQL create by Salvatore Sanfilippo

(@antirez)

The fastest data store available today (served entirely

from RAM)

Among the top 3 databases chosen by developers

Much more than a simple key/value - Strings, Hashes,

Lists, Sets, Sorted Set, LUA, transactions, Bits

operations

Strong use cases, dynamic community, large eco-

system

Redis

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100msec =

Fast apps requirements

max E2E response time, under any load

50msec = average Internet latency

50msec = required app response time (includes processing & multi DB accesses)

1msec = required DB response time

The only database to meet requirement

=

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DB performance comparison@<1mse

c

@<1msec

@<1msec

@<20msec

@<10-50msec

@<10-50msec

@<100msec

@<100msec

@>100msec

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Timeline

Followers

Caching

Messaging

Geo search

Leaderboards

Job management

RT analytics

Verticals & main use cases

Online advertisin

g

Social Gaming

Financial Services

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• Multi-TB in memory

• ~ 300,000 reads/sec

• ~ 5,000*N writes/sec

N - # of followers

Twitter

Every Timeline

(800 tweets per user)

is on Redis

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• 20TB+ in memory

• ~ 6,000,000 reads/sec

• ~ 600,000 writes/sec

Weibo (Chinese Twitter)

• Counting

• Reverse cache

• Top 10 lists

• Last Index

• Relational list/Message Queue

• Fast transactions w/ LUA

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Pinterest

Object graph:

• Per user (Sorted Set w/ timestamp as

score)

store the users followed (explicit+

implicit)

store the user’s followers

(explicit+implicit)

• Per board

Redis Hash for storing explicit followers

Redis Set for storing explicit unfollowers

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Stack Overflow

Three levels of cache:

• Local cache (no persistence)

sessions, and pending view count

updates

• Site cache

hot question id lists, users acceptance

rates..

• Global cache

Inboxes, API usage quotas, …

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Github

• Redis is used for routing info

• Matching user repositories to server

names

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Hipchat

• Which users are in which room

• Who is online

• XMPP server balancing

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Youporn

Most data is found in Hashes with ordered Sets used to

know what data to show

(1) ZinterStore on:

{videos:filters:release}{videos:filters:orientation:straig

ht}

{videos:filters:categories(id)}{videos:ordering:rating}

(2) Perform a ZRANGE to get the pages we want and get

the list of video_ids back

(3) Start pipelining to get all the videos from Hashes

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Snapchat

• 500+ instances

• 15-50TB

• Running on GCE

400M messages/day

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Why Redis Labs ?

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Infinite seamless scalability

True high-availability

Stable top performance

Zero management

Users choose us because..

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We invested a lot…

• 20+ man-years spent on R&D

• 15 Redis experts on team

Optimal Redis deployment

environment

• [BOSH] Bootstrapping Redis Labs cluster (over EC2)

• [Redis Labs Console] Create a plan & set CF Credentials

• [CF]: Create & bind service • Show a working app (try.redis)

• SSO

The Demo

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Questions ?

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Thank You