Cascading 3.0 Supports Multiple Compute Fabrics for Running Enterprise Data Applications at the Speed of Business
SAN FRANCISCO – June 9, 2015 – Concurrent, Inc., the leader in data application infrastructure, today announced the general availability of Cascading 3.0, the most widely used application platform for building and deploying enterprise data applications on Apache Hadoop.
The data application technology landscape continues to rapidly evolve with new, state-of-the-art, compute fabrics but with varying degrees of maturity. Enterprises who have invested in Hadoop are seeking practical solutions that provide the degrees of freedom to solve simple to complex problems, all while ensuring their investments are protected against change and technical uncertainty. Organizations need an enterprise-grade data application platform to quickly build and consistently deliver these data products to the business.
Cascading 3.0 represents a milestone release for future-proofing investments in next-generation data infrastructure by allowing enterprises to take advantage of newer compute fabrics as they come available without taking on any inherent risks. Cascading 3.0 abstracts away the underlying platform, allowing users to execute against additional platforms, not just MapReduce. Users have unique portability across programming languages (Java, SQL, Scala), Hadoop distributions (Cloudera, Hortonworks, MapR) and now compute fabrics. Native support for Apache Tez is the first to be supported, with others to be quickly added.
Cascading 3.0 Sets the Bar for Enterprise Application Development
With more than 275,000 user downloads a month, Cascading is the de facto standard in enterprise application infrastructure technology. With tens of thousands of production deployments and millions of production jobs, Cascading is relied on by the largest data-centric businesses, supported by key strategic partnerships with Hortonworks and broad support with all major Hadoop distributions. Cascading accelerates and simplifies enterprise application development, and meets a variety of enterprise use cases – ranging from simple to complex.
Cascading 3.0 is a major leap forward in enterprise data-centric application development. Features and benefits include:
- Allows enterprises to build data applications once, and run applications on the compute fabric that best meets their business needs
- Supports local In-memory, MapReduce and Apache Tez
- Delivers a flexible runtime layer for new computation fabrics to integrate and adhere to the semantics of a given compute engine, such as MapReduce or any DAG-like model through its pluggable query planner
- Provides benefits through portability to third-party products, data applications, frameworks and dynamic programming languages built on Cascading
- Supports compatibility with all major Hadoop vendors and service providers, including Altiscale, Amazon EMR, Cloudera, Hortonworks , MapR and Qubole, among others
Concurrent is leading the market in big data application infrastructure with Cascading and Driven, the industry’s leading performance management product for the data-centric enterprise. With Cascading at the core, Concurrent continues to meet customer demand for state-of-the-art technologies, while balancing the pragmatic needs for enterprise application development, forging important industry partnerships and making data-driven application development simpler, faster and smarter. Together, Cascading and Driven deliver a one-two punch to knock out the complexity and provide a proven reliable solution for enterprises to execute their big data strategies.
“Thanks to Cascading’s new TEZ engine, we were able to increase the processing speed of our main workload by a factor of 2x in production, and upwards of 10x in integration testing, compared to the traditional Hadoop MAPREDUCE engine. This acceleration was achieved with no significant changes to our application code, which is written in Scala using the Scalding framework. This spectacular improvement enables us to delay increasing the size of our cluster, improve turnaround time and at the same time enforce integration testing multiple times per hour, which is essential to ensure the quality and trustworthiness of our solution in a cost-effective way. To sum up, this collaboration allowed us to highly improve the quality and delivery of our service to our clients – Transparency RM offers Business Intelligence services and real online uses certification in a big data context. We look forward to the next adventure!”
– Cyrille Chépélov, Chief Innovation Officer, Transparency RM
“BloomReach standardized on Cascading as our data application development framework because it was easy to use and accommodated our scalability requirements. With terabytes of data processed every day by thousands of jobs, combined with rapid application iteration to deliver the best discovery experience to over 75 million consumers monthly, we require a flexible, scalable and efficient application development framework and chose Cascading. We are excited to see Cascading 3.0 hit this milestone so we can start testing out even better performing compute fabrics like Tez and Spark.”
– Amit Aggarwal, head of development, BloomReach
“We have transformed how brands and agencies effectively develop and deploy mobile marketing campaigns and we did that by transforming ad performance analytics. Instead of sampling, we process data sets that include over 30B data points to derive exactly how ads performed. We developed our innovative analytics applications such as Attribution and Report Builder using Cascading and Driven. The Cascading application development platform enabled us to manage our development process and increase developer productivity by 10x over hand coding in MapReduce. It organizes our code to promote reuse and standardization, which made it easier for us to build highly resilient, enterprise quality applications from day one. Cascading 3.0 is an exciting milestone as it delivers a truly future-proof application development platform so we can explore other computing fabrics to solve the next problem without retooling and retraining.”
- Mikhail Izrailov, big data specialist, Medialets
“With reported improvement gains of up to 15 times faster execution time, Tez and Scalding seem to be really delivering from Cascading’s perspective, as new execution fabrics are proving that Cascading and Scalding are enterprise ready, on a path of continuous improvement and can withstand the exciting claims from the growing community of Spark users.”
– Antonios Chalkiopoulos, author of “Programming MapReduce with Scalding” book
“This new, available version of Cascading will enable our users even further by simplifying application development, accelerating time to market and allowing enterprises to leverage existing, and more importantly, new and emerging data infrastructure and programming skills.”
– Chris Wensel, founder and CTO, Concurrent, Inc.
Availability and Pricing
Cascading version 3.0 is immediately and freely licensable under the Apache 2.0 License Agreement. To learn more about Cascading, visit http://cascading.org. Concurrent also offers standard and premium support subscriptions for enterprise use.
- Company: http://concurrentinc.com
- Cascading: http://cascading.org
- Driven: http://www.cascading.io/driven
- Contact us: http://concurrentinc.com/contact
About Concurrent, Inc.
Concurrent, Inc. is the leader in data application infrastructure, delivering products that help enterprises create, deploy, run and manage data applications at scale. The company’s flagship enterprise solution, Driven, was designed to accelerate the development and management of enterprise data applications. Concurrent is the team behind Cascading, the most widely deployed technology for data applications with more than 275,000 user downloads a month. Used by thousands of businesses including eBay, Etsy, The Climate Corp and Twitter, Cascading is the de facto standard in open source application infrastructure technology. Concurrent is headquartered in San Francisco and online at http://concurrentinc.com.
Kulesa Faul for Concurrent, Inc.