Cloudera, Inc, has released Cloudera Altus, a Platform-as-a-Service (PaaS) offering that enables 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 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.
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.
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.
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
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, etc.