Cloudera optimized for the cloud, announced the upcoming beta release of Cloudera Altus Analytic DB. Cloudera Altus Analytic DB is the first data warehouse cloud service that brings the warehouse to the data through a unique cloud-scale architecture that eliminates complex and costly data movement. Built on the Cloudera Altus Platform-as-a-Service (PaaS) foundation, Altus Analytic DB delivers instant self-service BI and SQL analytics to anyone, easily, reliably, and securely. Furthermore, by leveraging the Shared Data Experience (SDX), the same data and catalog is accessible for analysts, data scientists, data engineers, and others using the tools they prefer – SQL, Python, R - all without any data movement.
For many enterprises, challenges with existing analytic environments have resulted in a number of limitations for both business analysts and IT. Constraints on resources mean critical reporting and SLAs are given priority while limiting self-service access for other queries and workloads. To support additional workloads and access beyond SQL, data silos have proliferated, resulting in inefficiencies managing the multiple data copies, difficulties in applying consistent security policies, and governance issues. While business users struggle to analyze data across these silos and limiting the ability to collaborate with groups including data scientists and data engineers.
Cloudera Altus Analytic DB removes those limitations through the speed and scale of the cloud. Central to Altus Analytic DB is its unique architecture that brings the warehouse to the data, enabling direct and iterative access to all data in cloud object storage. This simple, yet powerful design delivers dramatic benefits for IT, business analysts, as well as non-SQL users.
· IT benefits from simple PaaS operations to easily and elastically provision limitless isolated resources on-demand, with simple multi-tenant management and consistent security policies and governance.
· Business analysts get immediate self-service access to all data without risking critical SLAs, and with predictable performance no matter how many other reports or queries are running. Additionally, they can continue to leverage existing tools and skills, including integrations with leading BI and integration tools such as Arcadia Data, Informatica, Qlik, Tableau, Zoomdata, and others.
· With no need to move data into the database, shared data and associated data schemas and catalog are always available for iterative access beyond just SQL, so data scientists, data engineers, and others can seamlessly collaborate.
“With Cloudera’s unique architecture, we have helped our customers modernize their data warehouse both on-premises and in cloud environments,” said Charles Zedlewski, senior vice president, Product at Cloudera. “Cloudera Altus Analytic DB continues that trajectory, making it even easier for analysts to get dedicated, self-service access for BI and SQL analytics, all with an enterprise focus. With no need to move data into the Cloudera Altus platform, users can quickly spin up clusters for business reporting, exploration, and even use Altus Data Engineering to deploy data pipelines, all over the same data and Shared Data Experience without impacting performance or SLAs.”
Key Capabilities of Cloudera Altus Analytic DB
Cloudera Altus Analytic DB, built with the leading high-performance SQL query engine, Apache Impala (recently graduated to a Top-Level Project), puts the full power and flexibility of a modern, cloud-powered analytic database in the hands of businesses quickly, easily, reliably, and securely:
● Brings the data warehouse to the data: No need to move data into the database – saving time and simplifying IT management and security.
● Delivers instant analytics: With no pre-processing or moving data, users can operate on data immediately and iterate – again and again – for faster time-to-insights.
● Ensures data consistency: Everyone works with the same data, schemas, and structures – business analysts, financial analysts, data scientists, data engineers, anyone.
● Goes beyond SQL: Flexible self-service access lets users collaborate over shared data, using the languages and tools they prefer to work with - SQL, Python, R, and more.
● Built with cloud scale: Easy elasticity and performance for fast, adaptable, cost-effective analytics.