Categories: NewsData

Cloudera Altus Analytic DB: Modernizing the cloud-based data warehouses

3 min read

Cloudera has announced the beta release of Cloudera Altus Analytic DB, a data warehouse cloud service that brings the warehouse to the data through a unique cloud-scale architecture that eliminates 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 users in a reliable and secure environment. In addition, 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 – without any data movement.

For enterprises, challenges with existing analytic environments have resulted in a number of limitations for both business analysts and IT. Because of resource constraints, 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 in organizations, resulting in inefficiencies in managing the multiple data copies, difficulties in applying consistent security policies, and governance issues. In turn, business users are struggling to analyze data across these silos and there is limited 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 could deliver 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.

Senior vice president Charles Zedlewski said Cloudera is helping its customers “modernize their data warehouse both on-premises and in cloud environments” with the unique architecture.

“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,” he said, stressing on how the Cloudera Altus Analytic DB is making it easier for analysts to get dedicated, self-service access for BI and SQL analytics, all with an “enterprise focus.”

Key Capabilities of Cloudera Altus Analytic DB

Cloudera Altus Analytic DB, built with the leading high-performance SQL query engine, Apache Impala (now 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.

The initial beta of Cloudera Altus Analytic DB will be available on Amazon Web Services (AWS). Sign up here to join the beta.

Abhishek Jha

Writes and reports on lnformation Technology. Full stack on artificial intelligence, data science, and music.

Share
Published by
Abhishek Jha

Recent Posts

Top life hacks for prepping for your IT certification exam

I remember deciding to pursue my first IT certification, the CompTIA A+. I had signed…

3 years ago

Learn Transformers for Natural Language Processing with Denis Rothman

Key takeaways The transformer architecture has proved to be revolutionary in outperforming the classical RNN…

3 years ago

Learning Essential Linux Commands for Navigating the Shell Effectively

Once we learn how to deploy an Ubuntu server, how to manage users, and how…

3 years ago

Clean Coding in Python with Mariano Anaya

Key-takeaways:   Clean code isn’t just a nice thing to have or a luxury in software projects; it's a necessity. If we…

3 years ago

Exploring Forms in Angular – types, benefits and differences   

While developing a web application, or setting dynamic pages and meta tags we need to deal with…

3 years ago

Gain Practical Expertise with the Latest Edition of Software Architecture with C# 9 and .NET 5

Software architecture is one of the most discussed topics in the software industry today, and…

3 years ago