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Dremio Corp., developer of a self-service data analytics technology based on the Apache Arrow in-memory columnar data processing framework, today announced a version of its product delivered as a managed cloud service.
Dremio Cloud leverages a no-copy data architecture that enables analytics users to access data in a data lake without extensive transformation and schema development. A data lake is a centralized data repository that holds both structured and unstructured data.
The company terms its platform a “SQL lakehouse,” borrowing a term created by Databricks Inc. to describe a system that applies data warehouselike structure to semistructured data. The company says its query engine enables high-performance SQL queries to be applied directly to cloud storage without copying or massaging the underlying data. Dremio works with a variety of front-end business intelligence tools.
“In the past, you had to size for capacity. Now you don’t worry about that because S3 is infinitely scalable,” said Tomer Shiran, Dremio’s founder and chief product officer, referring to Amazon Web Services Inc.’s object storage service.
The cloud service removes much of the manual configuration overhead from the user, Shiran said. “It’s a frictionless software-as-a-service with a global control plane,” he said. “You don’t have to deploy or manage software or worry about configuration. We take care of scalability, adding or taking away compute capacity based on your workload.”
Dremio, which closed a $135 million funding round early this year, said the managed cloud service is currently structured to work only with cloud data. The company will continue to sell an on-premises version of its product, although Shiran said 80% of its customers have already deployed the software in the cloud. “Over time, most customers who are already in the cloud will probably migrate to our managed service,” he said. “On-prem is a very small fraction of the business.”
An automatic onboarding option quickly and securely establishes the necessary connection to the user’s AWS account, allowing data consumers to connect via their favorite tools and instantly start querying data, Dremio said. There is no software to install, configure or upgrade, and no infrastructure to size, manage or monitor.
The control plane’s cloud-native microservices architecture provides limitless query planning capacity, while the data plane’s multiengine, multireplica architecture automatically scales based on workload, with customers charged nothing during idle times, the company said.
Data is encrypted both at rest and in motion and role-based access control enables users to define privileges on every dataset and object. They can also use existing user and group definitions already defined in cloud identity management systems such as those from Okta Inc.
The service is initially launching on AWS but support for Microsoft Corp. Azure will follow “within a couple of quarters,” Shiran said. Dremio also expects to offer a cross-cloud version that works across both AWS and Azure infrastructure.
Pricing will be usage-based depending upon the size of the data set and the number of queries. Dremio declined to provide more details.
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