Yellowbrick Data scales its cloud data warehouse across public clouds
Data warehouse provider Yellowbrick Data Inc. announced an updated version of its cloud platform today, saying it can scale more effectively as customer’s data needs grow.
It’s also introducing what it says is a unique pricing model that offers customers more predictable costs.
Yellowbrick offers both cloud- and on-premises-based data warehouses to enterprises, complete with services based on a massively parallel processing analytics database. The platform can run in customers’ own data centers, in the public cloud or in both environments at the same time. But it’s not just flexibility Yellowbrick offers, as it says its platform can run some types of queries up to 100 times faster than competitors, which include Google Cloud’s BigQuery and Snowflake Inc.
With today’s update to the cloud-hosted version of its data warehouse, the company said, it can now be deployed on-premises, in Amazon Web Services, Microsoft Azure and Google Cloud, or directly as a database platform-as-a-service in customer’s own public cloud accounts. Yellowbrick added that it now offers true separation of compute and storage, allowing for more elastic scaling on demand.
Yellowbrick was available on AWS previously, but only as a single-node deployment, Constellation Research Inc. analyst Doug Henschen told SiliconANGLE. “The multinode service with full separation of compute and storage is new, and it supports scaling in single-node increments up to 128 nodes,” he explained. “Also new, once available in the third quarter, will be support for Azure and Google, putting the ‘multi’ in multicloud support.”
In addition, Yellowbrick said, it has created a unified control plane that’s powered by Structured Query Language, with support for provisioning, management, monitoring and cost-control access across any topology.
Henschen said this addition is the realization of Yellowbrick’s vision to harness Kubernetes to provide a single pane of glass across hybrid and multicloud or cross-cloud deployments. As a result, administrators will now be able to provision Yellowbrick’s data warehouse in the cloud or on-premises and manage resources through this single pane of glass, he explained.
“Data scientists and analysts have a new SQL editor and data loading workflows that are said to make it easier to develop, iterate and test new use cases,” Henschen added. “On public clouds, the Yellowbrick service can run in the customers own cloud account on the provider’s Kubernetes service, so data ownership is always and only in the hands of the customer.”
The company makes further claims too, saying its cloud data warehouse can eliminate challenges around regulatory compliance and security as there is now shared metadata or services to worry about. It can also now integrate with data lakes using Parquet as a data interchange format and, finally, customers can choose to pay on-demand or through a fixed-capacity subscription.
“Support for the Parquet data format is new and is pretty crucial to compatibility with data lakes,” Henschen said. “Support for data formats was previously limited to CSV and compressed CSV.”
Yellowbrick Chief Technology Officer Mark Cusack said the data integration feature is important, because companies that have transitioned to the cloud have found themselves struggling to manage a complex set of incompatible data management and analytics systems. “Yellowbrick’s modern, elastic data warehouse helps organizations remove complexity by providing the same performance, functionality and unified user experience in their own data center, in public clouds and in a hybrid combination of both,” he promised.
Whichever way they decide to pay, customers will surely benefit from more predictable pricing and lower costs, the company said. Yellowbrick offers a guarantee on its website that it will provide enterprises with savings of at least 50% if they switch from Snowflake to its platform. Its cheapest subscription tier starts at just $10,000 per month, providing full access to all of the key features on its platform with a 10-terabyte limit per deployment.
By positioning itself at a lower price point than its competitors, Yellowbrick has managed to carve out a niche among smaller firms that require advanced data warehouse features without the need to store petabytes of information.
Image: Yellowbrick Data
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