See who is using MemSQL

The Database for Speed, Scale & Simplicity
MemSQL is a distributed in-memory and column store database for real-time and historical Big
Data analytics. Our fast data processing allows you to extract greater value and deeper
insights in real time.
Key Features
• Rapid data load and query execution
• Easy horizontal scale-out on commodity
hardware
• Familiar SQL interface
• Mixed OLTP and OLAP workloads
• Support for relational and JSON data
Use Cases
• AdTech
• Real-time bidding & attribution
• Recommendations
• Financial Services
• OMS, risk management
• Ecommerce
• Performance monitoring
• Fraud detection
• Recommendations
• Event & Machine Data
• Machine data collection
© 2014 MemSQL - Confidential & Proprietary 2

What Analysts Are Saying about MemSQL
“While SAP draws so much attention to in-
memory databases by marketing their
Hana database, MemSQL seems to be a
less expensive and more agile solution in
this space.” — Svetlana Sicular
“With it’s in-memory database, MemSQL is
well positioned to enable organizations to
analyze operational data in real time and attain
operational insights faster.” — Matt Aslett
“MemSQL adding true SQL-based access to
JSON promises to bring analytical response
to multi-structured datasets in a way that will
be difficult to match.” — John Myers
“MemSQL delivers extreme performance
at scale… whether running on commodity
hardware or in the cloud.” — Nik Rouda

MemSQL Delivers Results
“MemSQL is the right platform to handle our scale and provide real-
time insights, allowing us to effectively manage our infrastructure
and prevent anomalies.” — VP Technical Operations
“The new capabilities in MemSQL v3.0 allow CPXi to leverage
historical data stores and use them to shape real-time responses.”
— SVP Product & Technology
“MemSQL’s in-memory clustering architecture allows us to gain fast
insights fro our Big Data at scale, which is critical to growing our
business and increasing player value.”
— GM of Platform & Engineering
“We were looking for a solution that would keep up with the amount
of data that we process and MemSQL was the only solution that fit
all of our needs.” — Software Engineering Manager

Comcast: Real-Time Intelligence and Monitoring
• Background: Comcast is the largest
mass media and communications
company in the world. Its VIPER team
was created to deliver IP video to Apple,
Microsoft, and Samsung devices.
• Challenge: The VIPER team needed a
fast, scalable database for real-time
intelligence. The team needed to
monitor the health of streaming video
data for millions of users and respond
immediately to any glitches in their
system.
Solution:
• Comcast removed the disk I/O
bottleneck for streamlined real-time
calculations.
• MemSQL allows Comcast to aggregate
statistics across their entire database
white simultaneously executing complex
analysis.
• MemSQL’s horizontally-scaled platform
results in deeper analysis, faster results
and subsequent action.
Headquarters Industry Size
Philadelphia, PA Media 126,000

Zynga: Accelerating Data for Multi-Player Gaming
• Background: Zynga develops social
games such as Farmville and Words
with Friends that have millions of active
daily users.
• Challenge: Zynga needed a faster,
more scalable database to serve real-
time recommendations and ads, and to
create advanced multi-player games.
Solution:
• MemSQL allows Zynga to make
decisions based on billions of data
points on millions of users in real time.
• By deploying more than 600 nodes,
Zynga can store weeks of game data in-
memory, instantly recalling it to make
informed real-time decisions.
• Zynga developers can make real-time
in-game decisions based on players’
engagement levels with new game
extras or interactions with other players.
San Francisco, CA Gaming 1,300

CPXi: Real-Time Bidding for Faster, More Targeted Ads
• Background: CPXi is a global digital
media company that connects
consumers and brands, serving over 6
billion impressions per day.
• Challenge: Data ingest speeds were too
slow to support demanding, real-time
bidding. CPXi needed a solution that
could scale with demand and meet
demanding SLAs.
• Solution:
• MemSQL reduced CPXi’s ETL
processing tasks from 12-24 hours to
just seconds.
• Switching from Hadoop to MemSQL
allowed CPXi to cut 50 percent of their
EC2 instances and 50 TB of storage in
Amazon Cloud, saving hundreds of
thousands of dollars per year.
• MemSQL is helping CPXi built a data-
driven culture by making data accessible
to everyone in the organization through
a familiar SQL interface.
New York, NY AdTech 150

• Background: Shutterstock is a stock
photography agency that maintains a
library of 30 million stock photos, vector
graphics, illustrations, and video clips.
• Challenge: Data ingest speeds were
unable to support full real-time
dashboards and comparisons against
historical data for Shutterstock’s
massive globally-distributed operations
platform.
Solution:
• MemSQL allows Shutterstock to collect
more than 20 thousand data points per
second and query the data
simultaneously.
• Shutterstock is now able to monitor
thousands of servers and can view
trends and anomalies with real-time
series visualization.
• Shutterstock uses MemSQL as the
backbone of their real-time monitoring
system to prevent outages and
downtime, which saves the company
thousands of dollars per year.
New York, NY Internet 400
Shutterstock: Real-Time Operations Analysis

Kurtosys: Real-Time Risk Reporting for Asset Mangers
• Background: Kurtosys is a global
provider of digital marketing and client
reporting tools that help asset managers
attract and retain investor assets.
• Challenge: Kurtosys needed a system
to serve concurrent reads for thousands
of asset managers, as multiple clients
needed to be able to access information
simultaneously. The database solution
also needed to be able to scale with the
workload and support JSON data.
Solution:
• Kurtosys is able to query relational and
JSON data together with SQL without
performing ETL, enabling real-time
analytics on data feeds of variable
structure. Kurtosys is able to deliver faster,
more accurate reports to their customers.
• Kurtosys no longer must write application
code or de-normalize data for every JOIN
in an object database.
• MemSQL’s ability to scale out horizontally
on commodity hardware ensures that
Kurtosys now has the ability to meet SLAs
and scale as demand grows.
London, UK FinTech 100

Ziff Davis: Managing Web Properties
• Background: Ziff Davis is a leading
media company specializing in the
technology market. The company uses
an advanced ad-targeting platform,
focusing on over 50 million buyers each
month.
• Challenge: Previous NoSQL databases
weren’t providing the performance or
structure needed to efficiently manage
their web properties.
• Solution:
• MemSQL ensures rapid processing of
billions of events and 65 million URLs
with sub-second response times.
• MemSQL is now the backbone of Ziff’s
distributed audience analysis process,
generating specific profiles to determine
buying patterns and levels of interest
across their eight web properties.
• MemSQL allows Ziff Davis to expand
the capacity of their cluster without
taking the database offline; Ziff can now
scale quickly and easily as demand
fluctuates.
New York, NY AdTech 500

Clarity Services: Real-Time Fraud Detection
• Background: Clarity Services is the
leading real-time credit bureau,
providing fraud detection and credit risk
management solutions.
• Challenge: Provide fraud detection and
credit risk management in real-time by
coupling traditional credit-check sources
with proprietary information on subprime
consumer data.
Solution:
• MemSQL allows Clarity Services to run
thousands of unique queries and JOINs
against large data sets to continuously
provide the latest real-time credit
information from all of their algorithms and
data sources.
• Zero downtime is a must. MemSQL gives
Clarity the durability and multi-site
capabilities to ensure their providers never
have issues running credit checks.
• The application is primarily Ruby on Rails;
all Ruby tools and code work flawlessly
with out-of-the-box MemSQL.
Clearwater, FL Finance 100

• Background: Established in 2010,
Tradelab optimizes adtech display
campaigns for digital advertising
agencies.
• Challenge: Tradelab’s NoSQL database
was introducing cost and latency to the
real-time bidding process. The company
wanted to store more data in memory
without sacrificing performance.
Solution:
• MemSQL replaced Tradelab’s NoSQL
database and allows the company to
store more data in memory.
• MemSQL allows Tradelab to achieve
speeds more than 30 times faster than
before, close to the millisecond, while
simultaneously reducing cost and
latency.
• Tradelab now powers its proprietary ad-
tech technology with MemSQL; the
company has been able to optimize their
software performance and realize new
efficiencies of scale.
Paris, France AdTech 50
Tradelab: Accelerating Real-Time Bidding Software

Novus: Achieving Performance at Massive Scale
• Background: Novus is a portfolio
analytics platform for institutional
investors to analyze risk, performance,
and exposures.
• Challenge: Novus needed a powerfully
fast and reliable database to allow the
company to grow.
Solution:
• MemSQL provides Novus with a
massively scalable infrastructure that
allows instant access to data while
loading huge data volumes.
• Real-time analytics are no longer
blocked while writes are in process.
• MemSQL stabilized business operations
and provides reliable and simple
operational control.
• MemSQL provided a 10x performance
increase over Novus’ previous
MongoDB solution.
Paris, France AdTech 50

Thank you!
www.memsql.com
1.855.4.MEMSQL
Twitter: @MemSQL

See who is using MemSQL

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