Category Archives: Press Releases

Concurrent Launches Cascading 2.0

Press Releases

FOR IMMEDIATE RELEASE

Concurrent Simplifies Big Data Application Development and Management on Hadoop 

Introduces Cascading 2.0, the leading Java application framework for building enterprise Big Data applications on Hadoop

SAN FRANCISCO – June 5, 2012 – Concurrent, Inc., the enterprise Big Data application platform company, introduces Cascading 2.0, the application framework designed to enable Java developers to quickly and easily build Big Data applications on Apache Hadoop. An alternative API to MapReduce, Cascading has been proven in mission-critical applications, and has the support of a growing ecosystem of developers, partners and customers around the world.

Introducing Concurrent, Inc.

Concurrent was founded in 2008 to address the challenges surrounding the development, deployment and management of Big Data applications. Concurrent CEO and Founder Chris Wensel is the author of the Cascading open source project for data processing. Previously, he co-founded Scale Unlimited, the first Hadoop and Big Data-related professional services and training company, where he mentored large companies including Sun Microsystems, Apple and several others in Silicon Valley.

Concurrent is the company behind Cascading, the leading Java development framework for building enterprise Big Data applications on Apache Hadoop.

Introducing Cascading 2.0

Cascading 2.0 is an application framework that enables Java developers to quickly and easily build robust data processing and data management applications on Apache Hadoop that can be deployed on clusters running in the cloud or within private data centers. Available under the Apache 2.0 License Agreement, Cascading offers an alternate API to MapReduce to simplify Big Data application development and deployment.

Today, mission-critical applications already depend on Cascading. Recognized companies like Airbnb, Etsy, FlightCaster, iCrossing, Razorfish, Trulia, TeleNav and Twitter are just some examples where Cascading is being used to streamline data processing, data filtering and workflow optimization for large volumes of unstructured and semi-structured data. With a quickly growing community around it, Cascading is also at the core of popular language extensions including PyCascading, Scalding and Cascalog (open source projects sponsored by Twitter) and tools including CloudFront LogAnalyzer (developed by Amazon).

The Cascading framework is designed for data scientists, Hadoop administrators and application developers alike, to collaborate and rapidly develop and deploy scalable Big Data applications. Using the Cascading 2.0 API:

  • Data scientists can easily discover, model and analyze both unstructured and semi-structured data in any format and from any source such as flat files, key value stores and NoSQL and relational databases.
  • Hadoop administrators can seamlessly move and scale application deployments from development to test and production clusters regardless of cluster location or data size.
  • Application developers can more quickly build and test applications on their desktops in the language of choice (Java, Jython, Scala, Clojure or Jruby) with familiar constructs and reusable components, and instantly deploy them onto clusters of hundreds of nodes.

Supporting Quotes

“Building applications on Hadoop, despite its growing adoption in the enterprise, is notoriously difficult. We are driving the future of application development and management on Hadoop, by allowing enterprises to quickly extract meaningful information from large amounts of distributed data and better understand the business implications. We make it easy for developers to build powerful data processing applications for Hadoop, without requiring months spent learning about the intricacies of MapReduce.”
-Chris Wensel, CEO and Founder, Concurrent, Inc.

“Cascading has proven to streamline complex development on Hadoop. We support the future of Big Data analytics, and technologies like Cascading that help drive more data-driven, predictive enterprises. We already distribute Cascading as part of our Greenplum MR distribution, and plan to increase our integration and support with other offerings in the future.”
-Mike Maxey, Senior Director of Product Marketing of Greenplum, a division of EMC

“MapR shares a commitment to the growing, innovative and rich Hadoop development community. Cascading is already integrated and distributed as part of our MapR Distribution, and is widely used across organizations that depend on Big Data analysis. Cascading lets enterprise developers focus on the business of applications and data processing, while handling the complexities of development.”
-John Schroeder, CEO and Co-Founder, MapR Technologies

“Microsoft is committed to compatibility with Apache Hadoop for our upcoming Hadoop-based services on Windows Server and in the Windows Azure cloud. In testing, Cascading on Windows Server worked directly out of the box and we are certifying Cascading 2.0 on Windows Server to give Microsoft customers a flexible Big Data application development framework for Hadoop that lets them build and deploy applications for Apache Hadoop on Windows Server and Windows Azure.”
-Bob Baker, Director and Partner, Channel Marketing, Microsoft

“Cetas is pleased to partner with Concurrent to facilitate the complex workflows typically performed in Hadoop environments for in-depth analytics.”
-Muddu Sudhakar, Vice President, Cloud and Big Data Analytics, VMware/Cetas

Supporting Resources

Availability and Pricing

Cascading 2.0 is available now, and freely licensable under the Apache 2.0 License Agreement. Concurrent offers standard and premium support subscriptions for enterprise use, with pricing based on number of users. To learn more about Concurrent’s offerings please visit http://www.concurrentinc.com/newsletter.

About Concurrent, Inc.

Concurrent, Inc. is the enterprise Big Data application platform company. Founded in 2008 by Chris Wensel, the author of the popular open source Cascading API, Concurrent simplifies Big Data application development, deployment and management on Apache Hadoop. Concurrent is based in San Francisco and funded by Rembrandt Venture Partners and True Ventures. Visit Concurrent online at http://www.concurrentinc.com.

Media Contact
Kelly Indrieri
Kulesa Faul for Concurrent, Inc.
+1 (650) 340 1983
concurrent@kulesafaul.com

Large Companies Depend on Cascading to Run Their Business

Press Releases

FOR IMMEDIATE RELEASE

Large Companies Depend on Amazon Elastic MapReduce and Cascading to Run Their Business 

Airbnb, Etsy and The Climate Corporation Improve Business Productivity and Profitability Using Cascading with Amazon Elastic MapReduce

SAN FRANCISCO – August 15, 2012 – Concurrent, Inc., the enterprise Big Data application platform company, today announced that Airbnb, Etsy and The Climate Corporation are combining Cascading, an advanced Java application framework from Concurrent, with Amazon Elastic MapReduce (EMR), a managed Hadoop environment, to reduce the cost and complexity of building, deploying and managing advanced data processing applications on Apache Hadoop.

By simplifying development and data processing of their application workflows, these and other successful, service-oriented companies realize significant productivity and time-to-market benefits, while reducing infrastructures cost and complexity. As a result, Airbnb, Etsy and The Climate Corporation are able to focus on improving customer experience and value for their businesses.

Cascading is an advanced Java application framework that enables developers to quickly and easily build robust data processing and data management applications on Apache Hadoop that can be deployed on clusters running in the cloud or within private data centers. Amazon EMR is a cloud service that enables businesses, researchers, data analysts and developers to easily and cost effectively process vast amounts of data. Airbnb, Etsy and The Climate Corporation are using Cascading on Amazon EMR to power the critical applications that run their business today.

Together, Cascading and Amazon EMR deliver benefits including:

  • Simplified application development and deployment on Apache Hadoop
  • Greater control for data scientists to program in their favorite languages
  • Flexible and scalable infrastructure that can be provisioned on-demand
  • Significant cost and time savings when processing data-intensive applications

Supporting Quotes

“Cascading is a proven Big Data application framework that has been battle tested in rigorous production environments for many years. Developers rely on Cascading and the growing ecosystem of community sponsored projects to build complex data intensive applications that drive their business. Working with Cascading and Amazon EMR, customers can be instantly productive and can easily scale their application infrastructure to meet the growing needs of their businesses.”
– Chris Wensel, CEO and Founder, Concurrent, Inc.

“Our business, as a trusted community marketplace showcasing unique accommodations around the world, has been rapidly growing since 2008. Things happen fast around here, and we need technology that can keep up with such a dynamic business. Using Cascading on Amazon EMR, new applications are easier to test, and developer confidence in those applications is stronger. Data from these applications is used by analysts to determine factors driving room bookings as well as user drop-off, thus helping us improve customer experience and add business value.”
-Florian Leibert, Software Engineer and Developer at Airbnb

“Etsy is one of the fastest growing online marketplaces with over 40 million unique visitors per month generating over 1.4 billion page views and large volumes of data. Using Cascading and Amazon EMR, the pipeline with which we process this data has scaled smoothly. Cascading powers all A/B analysis, a variety of analytics and dashboards, behavioral inputs to our search index, as well as many data-driven applications on our web site.”
-Matt Walker, Staff Software Engineer at Etsy

“The Climate Corporation builds massive, hyper-local weather and crop yield models, which are used to protect farmers from the financial impact of bad weather. We need to do this frequently and quickly. Cascading and Amazon EMR, via the Cascalog framework, enable our team of data scientists to focus on their strength — building these models — while hugely reducing the operational overhead traditionally associated with large-scale distributed computing. We process more than twenty (and growing) independent scientific datasets, resulting in terabytes of model data. It’s hard to imagine being anywhere near this productive without Cascading and EMR.”
-Siraj Khaliq, CTO at The Climate Corporation 

Supporting Resources

About Concurrent, Inc.

Concurrent, Inc. is the enterprise Big Data application platform company. Founded in 2008 by Chris Wensel, the author of the popular open source Cascading API, Concurrent simplifies Big Data application development, deployment and management on Apache Hadoop. Concurrent is based in San Francisco and funded by Rembrandt Venture Partners and True Ventures. Visit Concurrent online at http://www.concurrentinc.com.

Media Contact
Kelly Indrieri
Kulesa Faul for Concurrent, Inc.
+1 (650) 340 1983
concurrent@kulesafaul.com

Concurrent, Inc. Partners with MapR

Press Releases

Concurrent, Inc. Partners With MapR to Expand Usage of Hadoop in the Enterprise

MapR now fully certified with Concurrent’s Cascading and will include Concurrent open source tool in Hadoop distribution

SAN FRANCISCO, CA – June 29, 2011 – Concurrent, Inc., today announced its partnership with MapR Technologies, Inc., to expand usage of Hadoop in the Enterprise. By combining MapR’s innovations to make Hadoop more reliable, affordable, manageable and easier to use with Concurrent’s Cascading that allows applications to work with Hadoop through a straightforward Java API, the two companies are bringing large-scale data analysis to the Enterprise.

Apache Hadoop open source has been adopted quickly in “new economy” companies, but the requirement to write and manage complex MapReduce jobs and inability to integrate the analytics with Enterprise applications have slowed broader adoption.

“I believe Enterprises have the most to gain from using Hadoop, but the Apache version hasn’t fully delivered on that promise,” noted Chris Wensel, CEO and Founder of Concurrent, Inc. “MapR is the first to make great strides towards this goal, and we believe using the Cascading API with a MapR foundation delivers on the full promise of Hadoop in the Enterprise.”

Under this partnership, the MapR distribution for Apache Hadoop has been certified compatible with Cascading and supported for production use by Concurrent’s customers. Also, the MapR distribution will include the open-source application Multitool, based on Cascading, which allows users to search, find and process data files from the command line across a Hadoop cluster similar to sed and grep in Unix without the need to write code for common tasks.

“MapR is committed to expanding the Hadoop ecosystem to further facilitate a growing, innovative and viral Hadoop community,” said John Schroeder, CEO and Co-Founder, MapR Technologies. “We’ve now fully certified the MapR distribution with Cascading, a tool that has helped drive industry momentum and is widely leveraged by organizations whose business depends on data analysis.”

Cascading has been widely adopted, with users including Twitter, StumbleUpon, Ion Flux and Etsy. Cascading allows companies to develop new capabilities quickly and get to market faster.

Read more about Cascading here.

About Concurrent, Inc.
Concurrent, Inc. provides Enterprise class software that brings the power of parallel computing clusters to production data processing. The company is headquartered in San Francisco, CA. For more information about Concurrent, Inc., please visit www.concurrentinc.com.