MemSQL Powers the Enterprise

The MemSQL database platform is solving some of the most difficult Big Data problems across a variety of industries. Customers are turning to MemSQL when their existing database technology underperforms or lacks the flexibility to deliver the speed, scale, and simplicity to maximize the value of their data.

MemSQL is proven across thousands of nodes in the most high-velocity Big Data environments in the world.

“With its in-memory database, MemSQL is well positioned to enable organizations to analyze operational data in real time and attain operational insights faster”

Matt Aslett, Research Director, Data Management and Analytics, 451 Research

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Hundreds of Companies Worldwide Run MemSQL.

MemSQL accelerates applications and powers real-time analytics at the most innovative and respected companies. Built on next generation database technology, our platform empowers organizations to make data-driven decisions and better engage customers.

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Case Studies

MemSQL has been adopted across the most demanding data-driven industries. Fortune 500 and mid-market companies are recognizing that MemSQL's unmatched performance and flexibility can accelerate applications, provide faster insights, and enable new real-time use cases. Below are some examples of how MemSQL is changing the way businesses manage and extract value from their data:

Zynga – Real-Time Data Warehouse

Background: Zynga develops social games such as Farmville and Words with Friends that have millions of daily active users.

Challenge: Zynga faced a significant challenge in the amount of data they needed to analyze, as the company’s previous database platform could not handle data ingest and deletes at scale. The company’s data loading and query speeds were too slow to produce fast insight from Big Data at scale.

Solution:

  • MemSQL allows Zynga to make decisions based on billions of data points in real-time to provide better in-game personalization and overall customer satisfaction.
  • By deploying hundreds of nodes, Zynga can perform week over week analysis of game data to analyze trends, make real-time recommendations, and identify issues immediately for better performance.
  • Zynga developers can make real-time in-game decisions based on players’ engagement levels with new game extras or interactions with other players.

CPXi - Real-Time Ad Bidding

Background: CPXi is a digital media holding company that saw tremendous growth in 2013, recently earning a spot on Forbes’ “America’s Most Promising Companies” list.

Challenge: Like many digital ad tech companies, CPXi sought to enhance their real-time bidding platform to ensure maximum return on investment during the bidding process. CPXi’s previous data ingest speeds were too slow to support the demands of true real-time bidding.

Solution:

  • MemSQL allows CPXi to ingest billions of streaming data points in real-time from different ad partners, reducing batched loads.
  • What used to take 12-24 hours, CPXi is now able to perform analysis on real-time and historical data in seconds — without ETL — to execute exact real-time ad bidding.
  • MemSQL’s tiered storage architecture allows CPXi to consolidate their complex real-time bidding infrastructure, with MemSQL doing what used to require several different components.

Comcast - Real-Time Intelligence

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. They needed to monitor the health of streaming video data for millions of users in real-time and be able to respond immediately to any unexpected latency or issues within the network.

Solution:

  • Comcast removed the disk I/O bottleneck for streamlined real-time calculations by ingesting data in real-time, eliminating the need for batch loads.
  • MemSQL’s simple database architecture allows Comcast to aggregate statistics across their entire database while simultaneously executing complex analysis.
  • With a fast growing team, MemSQL’s familiar SQL interface allows Comcast to quickly on-board new members into productive contributors faster than other database platforms.

Shutterstock — Real-Time Operations Analysis

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:

  • Shutterstock can now simultaneously ingest and query billions of data points in real-time, providing immediate insight into their globally-distributed operations platform.
  • Rather than simply storing content for post-analysis of reported site issues, Shutterstock uses MemSQL to analyze real-time and historical data together to identify potential issues before they occur.
  • MemSQL provides Shutterstock with graphical insights into the status, performance, and configuration of their MemSQL cluster, facilitating cluster management.

Ziff Davis – Managing Web Properties

Background: Ziff Davis, Inc. is a leading all-digital media company specializing in the technology market, reaching over 50 million in-market buyers every month.

Challenge: Due to the extremely high rate of both read and write transactions, Ziff Davis needed a database that would could handle not only the high volume of incoming data, but that would also allow Ziff Davis to query this data store with lighting-fast response times.

Solution:

  • MemSQL’s ability to scale horizontally on commodity hardware allows Ziff Davis to easily scale out their cluster based on demand in a way that is both cost-effective and efficient.
  • MemSQL enables Ziff Davis to ingest and query large volumes of data from 65 million URLs and billions of impressions to monitor which users view specific content across their network in real-time.
  • MemSQL provides the performance and structure Ziff Davis needs, as their previous NoSQL databases could not efficiently handle the company’s vast amounts of data.

Kurtosys – Information Management for Asset Managers

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.
  • With MemSQL, Kurtosys is no longer required to write application code or denormalize 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.