SOURCE: Unravel Data

Unravel Data

November 01, 2016 08:00 ET

Unravel Data Certified on Cloudera Enterprise

Unravel accelerates time-to-value of Big Data investments for Cloudera customers with Cloudera Enterprise 5 certification

MENLO PARK, CA--(Marketwired - Nov 1, 2016) -  Just two months after its launch out of stealth, Unravel Data today announced that its full-stack performance intelligence platform for optimizing Big Data operations (DataOps) has been certified on Cloudera Enterprise 5 through the Cloudera Certified Technology Program. Cloudera has the world's fastest, easiest and most secure data analytics platform built on Apache Hadoop for helping organizations solve their most challenging business problems with data. The Cloudera Certified Technology Program's goal is to simplify the process for Apache Hadoop technology buyers to purchase the right components and software applications to extract the greatest value from their data.

The certification provides Cloudera customers with a platform to accelerate Big Data applications, optimize resource usage and provide operations intelligence, all from one single location. The Cloudera Enterprise 5 certification ensures support for mutual Unravel Data and Cloudera customers when Unravel is used in a Cloudera environment. In addition, by leveraging capabilities through the Cloudera Manager Parcels, Cloudera customers can be confident that Unravel deployments on Cloudera clusters are seamless. 

"Unravel Data provides Cloudera customers with enterprise-grade software that enhances the management of applications on Cloudera Enterprise 5," said Tim Stevens, Vice President of Business and Corporate Development at Cloudera. "By leveraging Unravel Data combined with Cloudera, users can improve the reliability and performance of their Big Data applications by identifying bottlenecks and inefficiencies in real-time, while receiving predictive and actionable insights."

Nipping DataOps Performance Problems in the Bud
Until now, the enterprise has relied on raw logs and systems monitoring solutions to optimize their Big Data applications -- and as companies continue to adopt numerous Big Data technologies to help meet their business needs, complexity is only increasing as the time required to diagnose and resolve issues is growing exponentially. The primary challenge faced by the enterprise is finding a single full-stack platform capable of analyzing, optimizing and resolving any issues that exists with Big Data applications and the infrastructure supporting them.

Enter Unravel: Unravel addresses the unmet challenges of data teams that find themselves spending much of their day digging through machine logs in order to find the root cause of problems on a Big Data stack. These problems, if not eradicated, reduce application performance and divert teams from their real mission of deriving value from their Big Data. Unlike other platforms, Unravel resolves problems automatically, detecting and pinpointing performance and reliability issues with Big Data applications running on clusters scaling up to several thousand nodes. With just the click of a button, Unravel drastically accelerates time-to-value of Big Data investments.

For data teams working in a Cloudera environment, Unravel demystifies performance issues on a stack that typically hosts a lot of app engines, such as MapReduce, Hive, Spark, Oozie and others. Unravel has teamed with Cloudera to help enable organization to more effortlessly run applications on top of Cloudera. Cloudera provides the stack, while Unravel ensures that all of the processes and apps on the stack run optimally; furthermore, that budding issues are detected and resolved before they proliferate.

"The monitoring and management of Big Data applications is challenging and complex. By strategically leveraging data from across the stack, and then applying modern data science and machine learning principles, Unravel delivers a guided path to address issues related to performance, failures and resource utilization for Big Data applications," said Bala Venkatrao, Vice President of Products at Unravel Data. "With the certification of Unravel Data by Cloudera, we now provide our mutual customers with an intelligent platform for helping organizations get the most out of their Big Data investments, which comes only when they can effectively manage their Big Data Applications."

Availability
Unravel Data certified on Cloudera Enterprise is available now. Companies such as Autodesk and YP.com are already using Unravel Data to manage their production Big Data systems. Unravel Data is available immediately for on-premises, cloud or hybrid Big Data deployments. Unravel Data currently supports Hadoop, Spark and Kafka, with plans to add support for other systems such as for data ingestion (Storm, Flume), NoSQL systems (Cassandra, HBase) and MPP systems (Impala, Drill). Unravel Data fully supports secure deployments with Kerberos, Apache Sentry, Encryption, etc. For more information, please visit www.unraveldata.com.

Additional Information
Data sheet: www.unraveldata.com/datasheet.pdf
Case Studies: www.unraveldata.com/resources

About Unravel Data
Unravel Data automates and simplifies Big Data operations (DataOps) with a full-stack performance intelligence platform that accelerates application performance, optimizes multi-tenant resource usage, and provides operations intelligence -- all from a single location. Unravel Data supports popular Big Data systems such as Hadoop and Spark for both on-premises and cloud environments. Customers include leading Big Data practitioners such as Autodesk and YP.com. Unravel Data was founded in 2013 by Kunal Agarwal and Dr. Shivnath Babu when they experienced the frustration of manually troubleshooting performance problems in Big Data stacks firsthand. Unravel's founding team includes Big Data experts from companies such as Cloudera, Oracle, and Microsoft. Unravel Data has raised a total of $7.2 M in two rounds of funding from Menlo Ventures and Data Elite Ventures.

Copyright Statement
The name Unravel Data is a trademark of Unravel Data™. Other trade names used in this document are the properties of their respective owners.

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