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Managed Service for Data Engineers Delivers a Job-First Experience
and Reduces Cloud Migration Risk

STRATA DATA London, U.K. — May 24, 2017Cloudera, Inc, (NYSE:CLDR) the provider of the leading modern platform for machine learning and advanced analytics, announced the release of Cloudera Altus, a Platform-as-a-Service (PaaS) offering that makes it easier to run large-scale data processing applications on public cloud. The initial Altus service helps data engineers use on-demand infrastructure to speed the creation and operation of elastic data pipelines that power sophisticated, data-driven applications.

Data engineering applications like ETL (Extract, Transform and Load) or batch scoring are often large, batch-oriented workloads that run for a fixed period of time and help companies extract critical insights from raw data. Organizations can gain significant flexibility and efficiency advantages by running these pipelines on elastic infrastructure. Enterprises want to leverage cloud infrastructure alongside familiar large-scale data processing tools and technologies.

The Cloudera Altus Data Engineering service simplifies the development and operations of elastic data pipelines; putting data engineering jobs front and center and abstracting infrastructure management and operations that can be both time consuming and complex. Altus also reduces the risk associated with cloud migrations. It provides users with familiar tools packaged in an open, unified, enterprise-grade platform service that delivers common storage, metadata, security, and management across multiple data engineering applications.

“Data engineering workloads are foundational for today’s data-driven applications,” said Charles Zedlewski, senior vice president of Products at Cloudera. “Altus simplifies the process of building and running elastic data pipelines while preserving portability and making it easy to incorporate data engineering elements into more complex BI, data science and real-time applications.”

Cloudera makes it easy, cost-effective, and convenient to deploy these workloads on cloud providers, such as Amazon Web Services (AWS), taking advantage of cloud elasticity, low-cost storage and compute options, and rapid provisioning to deliver a modern data service that can tackle even the most challenging business problems. Cloud object stores such as Amazon Simple Storage Service (Amazon S3) are becoming increasingly popular for their resiliency, scalability, and relatively low cost.

According to IDC, public cloud deployments are now at 12% of the overall worldwide business analytics software market and expected to grow at a 25% CAGR through 2020[1]. Cloud is one of the fastest growing deployment environments for Cloudera customers, and Altus makes it easier than ever to run data engineering workloads in the cloud.

Features and benefits of Altus include:

  • Managed service for elastic data pipelines - Cloudera Altus is a PaaS that allows data engineers to easily and quickly provision Apache Spark, Apache Hive, Hive on Spark, and MapReduce2 capacity on cloud-native infrastructure. Altus presents intelligent default cluster settings and environments that dramatically reduce cluster deployment times and operations, automating processes like cluster provisioning, configuring, and termination.
  • Workload orientation - Cloudera Altus centers around data pipelines rather than clusters or infrastructures, so users can easily submit, clone, and troubleshoot pipelines with minimal attention paid to the underlying infrastructure.
  • No data siloes - The Altus Data Engineering service enables data engineers to run direct reads from and writes to cloud object storage as does the rest of Cloudera’s platform. This data is immediately available for use by other Cloudera workloads without requiring data replication, ETL or changes to file formats. In doing so users can more easily incorporate data engineering into their data science, BI and real time DB applications.
  • Backward compatibility and platform portability - Altus supports multiple versions of CDH, the most widely used open source platform in the industry. Users can easily move workloads to and from the cloud without needing to modify their applications. Because CDH is backward compatible across minor releases, customers can harness the latest innovation from the Apache big data open source community without fear of breaking their applications from release to release.
  • Built-in workload management - Altus automates and simplifies the common operational issues related to elastic data pipelines with workload management. Users can troubleshoot failed jobs with or without the clusters or compute infrastructure being present.  In addition Altus’ workload management flags significant performance deviations and proposes a root cause analysis. In doing so customers can run their data pipelines with greater reliability and lower cost.

The initial rollout of Cloudera Altus includes support for Apache Spark, Apache Hive on MapReduce2, and Hive on Spark. It is available today in most Amazon Web Services (AWS) regions. Over time Cloudera plans to expand Altus to support other leading public clouds such as Microsoft Azure. For more information or to review the reference architecture, please visit


Supporting Quotes


451 Research

"Data and analytics, particularly in the cloud, continues to be one of the most significant areas of growth and investment for many enterprises. But organizations also faces challenges with cloud-based cluster management, data processing, and migration, which is right where Cloudera is focusing its efforts with Altus.”

-- James Curtis, senior analyst, data platforms and analytics


Amazon Web Services

“Customers are increasingly choosing AWS for their large-scale data processing workloads. The Altus service on AWS will make it easier for Cloudera customers to take advantage of the cloud with on-demand data processing and cost optimization through Amazon Elastic Compute Cloud (Amazon EC2) Spot Instances.”

-- Ken Chestnut, global segment lead



“Altus gives us the ability to quickly and easily provision and deploy data engineering clusters on AWS, and enables our ETL developers to run their business-critical workloads without the hassle of ongoing cluster operations and management from CyberZ. We are also pleased to see that we can use the same enterprise technology stack in the cloud as is deployed on-premises to make our cloud migration that much easier.”

-- Takahiro Moteki, Big Data Architect of F.O.X



“We’re excited to be the first integration provider to support Cloudera Altus and enable our customers to deploy big data projects dramatically faster with far less operational support. Together with Cloudera, we are empowering organizations to transparently build big data integration jobs that can run on-premises or in the cloud, making it easier for them to run their business on their hybrid cloud and on-premise infrastructure.”
-- Ciaran Dynes, VP Products

[1] IDC MARKET FORECAST, Worldwide Business Analytics Software Forecast, 2016–2020

About Cloudera

Cloudera delivers the modern platform for machine learning and advanced analytics built on the latest open source technologies. The world’s leading organizations trust Cloudera to help solve their most challenging business problems by efficiently capturing, storing, processing and analyzing vast amounts of data. Learn more at

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Press Contact

Deborah Wiltshire


+1 (650) 644-3900


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