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October 10, 2015 11:53 AM ET


Company Overview of Cloudera, Inc.

Company Overview

Cloudera, Inc. provides enterprise data management solutions for big data applications. It offers CDH, an open source distribution solution for Apache Hadoop and related projects. The company also provides Cloudera Enterprise that includes Cloudera Manager, a management application for Apache Hadoop and the enterprise data hub to make administration of enterprise data hub simple and straightforward; and Cloudera Navigator, an integrated data management application for Apache Hadoop-based systems. In addition, it offers training services for developers, administrators, and data analysts. Further, the company provides enterprise solutions, such as data warehouse optimization, advanced analytic...

1001 Page Mill Road

Building 2

Palo Alto, CA 94304

United States

Founded in 2008





Key Executives for Cloudera, Inc.

Chief Executive Officer and Director
Age: 53
Chairman of the Board and Chief Strategy Officer
Co-Founder and Chief Technology Officer
Chief Financial Officer
Age: 50
Chief Architect
Compensation as of Fiscal Year 2015.

Cloudera, Inc. Key Developments

Deloitte Consulting LLP and Cloudera Announce Comprehensive Capital Analysis and Review Solution

Deloitte and Cloudera announced the availability of a solution built to address financial services industry (FSI) challenges meeting regulatory compliance of comprehensive capital analysis and review (CCAR). Deloitte's CCAR solution leverages Cloudera Enterprise to provide cost savings, operational efficiencies, and increased flexibility in financial services firms' regulatory data management environments to accommodate future regulatory changes. Maintaining the large volumes of data needed to perform stress tests has traditionally been a significant effort. This data grows rapidly, and as a result, periodic system upgrades are needed in order to increase memory and storage for quarterly and annual CCAR report processing and model development, validation, and archiving. Regulations are also continuously evolving. The annual CCAR supervisory rules specify new scenarios and datasets to be used in credit risk, liquidity risk, market risk, pre-provision net revenue (PPNR), and capital management models that generate the forecasted stress estimates. It can be costly and time consuming to integrate the data required for CCAR and then to develop and run the models quarterly, yearly, or even more often. To combat the difficulties associated with traditional CCAR solutions, Deloitte has harnessed the power of Hadoop through Cloudera Enterprise. The Deloitte-designed solution includes accelerators to streamline data selection, data quality, variables conversion, data ingestion and management, and to convert or migrate models to the SAS DS2 or Apache Spark/Python programming languages.

Cloudera Launches Kudu, New Hadoop Storage for Fast Analytics on Fast Data

Cloudera announced the public beta release of Kudu, a revolutionary new columnar store for Hadoop that enables the powerful combination of fast analytics on fast data. Complementing the existing Hadoop storage options, HDFS and Apache HBase, Kudu is the first native Hadoop storage engine that supports both low-latency random access and high-throughput analytics, dramatically simplifying Hadoop architectures for increasingly common real-time use cases. A public beta of Kudu is immediately available under the Apache open source license, and will be transitioned to the Apache Software Foundation incubator in the future. Until now, developers have been forced to make a choice between fast analytics with HDFS or efficient updates with HBase. Especially with the rise of streaming data, there has been a growing demand for combining the two features to build real-time analytic applications on changing data. Kudu complements the capabilities of HDFS and HBase, providing simultaneous fast inserts and updates and efficient columnar scans. This powerful combination enables real-time analytic workloads with a single storage layer, eliminating the need for complex architectures. Kudu's architecture streamlines the developer experience for building analytic applications - supporting common use cases that include time series analysis, machine data analytics, and online reporting. Additionally, Kudu is designed to take advantage of changing trends in hardware and in-memory processing. It delivers outstanding CPU performance, takes advantage of RAM and flash, and drives high I/O efficiency as a true columnar store. Finally, as a native, open component within Hadoop, Kudu is integrated with and provides faster query performance for the most powerful analytic frameworks. Users already rely upon many of them, including Impala and Spark - for end-to-end analytic applications in a single platform. Kudu was jointly engineered by Cloudera and Intel in advance of the changing hardware landscape. Intel has actively contributed to Kudu to help it take full advantage of current and future Intel processor and memory technologies. Kudu was designed to use new persistent memory (pmem) innovations being developed through Intel's pmem project. As an open source project, Kudu has drawn wide involvement from the community. Xiaomi has been one of the first beta users of Kudu and actively contributes to the project. Other organizations, including AtScale, Splice Machine and Zoomdata, have also been developing on Kudu.

Cloudera Enterprise Data Hub Edition Provides Enterprise-Ready Hadoop for the Microsoft Azure Marketplace

Cloudera announced that Microsoft Azure customers can now deploy Cloudera Enterprise, Data Hub Edition in the Azure Marketplace. Azure customers will have access to the full breadth and scope of Cloudera's enterprise Hadoop offering, which includes core Hadoop components for unified storage and parallel processing and premium offerings for data discovery and advanced analytics that serve a variety of use cases. Cloudera Enterprise, Data Hub Edition integrates with the Azure suite of BI tools including Microsoft Power BI so business analysts can discover, analyze, visualize, and model data in ways that yield unprecedented benefits.

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