Cloudera today announced the first instantiation of its enterprise data cloud, the Cloudera Data Platform, a native cloud service to manage data and workloads on any cloud.
Many enterprises are creating multi-cloud strategies but face increased complexities due to having some workloads in Microsoft Azure, for instance, while others live in Amazon or Google Cloud, and still other remain on-premises. Further, IT teams are concerned with regulatory compliance, while the business side wants to move fast, and reconciling these also can be difficult. “This leads to an inherent tension, where both sides are right — business wants to move fast while IT has to make sure that even when they move fast, they don’t break too many things, especially when it comes to regulations,” Arun Murthy, chief product officer at Cloudera, told SD Times.
Cloudera’s data platform is designed to deliver the analytics businesses require to manage their data and workloads, whether on-premises, in the cloud, or on the edge. As part of the launch, Cloudera also is introducing capabilities around three new cloud services: Cloudera Data Warehouse, Cloudera Machine Learning and Cloudera Data Hub.
According to the company, the Data Warehouse service “makes it fast and easy to deploy data warehouses for teams of business analysts with secure, self-service access to enterprise data.”
The Machine Learning service enables deployment of collaborative ML workspaces for data science teams with secure, self-service access, and the Data Hub is a data management and analytics service for building custom business applications, also with secure, self-service access to enterprise data.
As an example, Murthy described real-time billing as a use. “You want to look at your smartphone and see how many minutes you’ve used today. In that world, you need streaming ingestion, you need data transformation, you need reporting and you need machine learning so you can warn the user that they might be using more data or minutes than they should. So in that world, you need something with multiple functions. You just talked about streaming, data engineering, data warehousing and machine learning, coming together as one to deliver that value to the customer. That’s what drives the enterprise data cloud.”
With CDP, Murthy said, “you can actually consistently look at all your infrastructure, all your data, on prem or on multiple public clouds, move data back and forth, add consistent security and governance, and then on the same data set, one copy of the data, you can actually run multiple workloads. You can run machine learning, you can run warehousing and data engineering, and then security and governance works holistically across all of that.”
Murthy said Cloudera is in a unique position “at the intersection of multi-function analytics — data warehousing, engineering, machine learnings — and there are a lot of single-function vendors, and we don’t see a lot of on-premises and cloud.”
Cloudera Data Warehouse, Machine Learning, and Data Hub cloud services are available on AWS, while an on-premises CDP software option, CDP Data Center, is in tech preview for select customers and will be generally available later this year.