A noteworthy point is that Cloudera complements popular cloud services, such as Amazon Web Services (AWS) and Microsoft Azure. While cloud services do provide useful resources — such as compute instances and object storage on demand — Cloudera offers the unified platform to organize, process, analyze, and store data at large scale… anywhere. The same enterprise capabilities delivered on premises are optimized for cloud environments, taking advantage of the elasticity and delivering the self-service desired. Therefore, having a common, open standards-based data platform offers flexibility, avoiding lock-in to any proprietary service. As cloud vendors continue to compete with ever lower costs, data and analytics remain portable. This allows businesses to arbitrage the costs, and run workloads where they make the most sense.
There are two common ways to approach cloud services with Cloudera. The first is to “bring your own” Cloudera licenses to the cloud of your choice. Popular products like Cloudera Data Science Workbench, Analytic DB, Operational DB, and Essentials can be run natively in cloud environments, deploying the cloud service’s resources much the same way they would on-premises. Cloudera Director facilitates provisioning and management of clusters in the cloud. Simply choose the AWS or Azure compute instances, class of storage, and go.
The newer, second option is to leverage Cloudera Altus “data engineering-as-a-service,” which simplifies the experience by eliminating even the initial steps of installing software or configuring clusters. Instead, users can immediately begin to build data pipelines and run jobs for their applications. Either way, the Cloudera platform promotes a focus on driving business results, not troubleshooting the inevitable challenges that come with ensuring compatibility amongst pieced-together components. Cloudera products cooperate universally and smoothly across your choice of environments and applications.
A number of notable advantages come with a unified, all-encompassing data platform, which Cloudera calls the Shared Data Experience (SDX.) Security policies are set once and implemented uniformly upon data and users anywhere. Governance is handled evenly across all environments and applications, both for technical and business metadata. Self-service becomes easy with a unified view of who has rights to what types of data. While these goals sound simple, they are all but impossible to deliver if the analytics services aren’t designed holistically from the beginning, a common problem amongst other cloud data and analytics services. Retrofitting functionality across products adds complexity and risk, and often has limited to no capability to ensure enterprise standards are met.
Check back for Part 3 of 3, coming soon…