Teradata will offer a new version of its multi-cloud analytics platform VantageCloud with low-cost object storage along with expanded ClearScape Analytics suite that supports in-database analytics for artificial intelligence operations, it said on Monday.
Dubbed VantageCloud Lake and not to be confused with VantageCloud Enterprise edition, which is geared towards IT-managed enterprise workloads, the new self-service cloud-based platform is aimed at accelerating business outcomes for enterprises, especially smaller ad-hoc, exploratory, and departmental workloads, said Stephen Brobst, chief technology officer at Teradata.
“In the Lake (edition) we’ve optimized for low cost per terabyte for scanning types of workloads, which are sort of quick in-and-out operational intelligence kinds of workloads,” Brobst said, adding that the Lake edition can be scaled up or down as needed since its service level agreements (SLAs) are different from the enterprise edition’s.
These abilities, according to Teradata, could provide enterprises with advantages such as launching new projects across departments by leveraging core data, aligning compute resources across the platform and maintaining overall governance and cost control.
Some of the other features of VantageCloud Lake include workload management and workload isolation along with clear separation of compute and storage, and rolling updates that needs no downtime or intervention.
VantageCloud Lake Edition is available on AWS, Teradata said, adding that it will be available on all major public cloud services by early 2023.
Teradata could upend rivals with VantageCloud Lake
Teradata, which competes with the likes of Snowflake, AWS, Google Cloud, Microsoft, Oracle and IBM in the analytics platform space, could have an edge over its rivals with the launch of VantageCloud Lake, analysts said.
“VantageCloud Lake expands Teradata’s addressable market by complementing the VantageCloud Enterprise offering. Teradata is already well-engaged in data-intensive industries but VantageCloud Lake could lower the barriers to adoption by smaller companies and digital natives and strengthen Teradata’s competitive positioning in relation to other cloud-native analytics data platform offerings,” said Matt Aslett, vice president and research director at Ventana Research.
The new product does a one-up on Snowflake as it offers a more modern architecture harnessing low-cost object storage and cloud-native serverless scaling, said Doug Henschen, principal analyst, Constellation Research.
“VantageCloud Lake delivers the simple self-service deployment and serverless auto-scaling capabilities that Snowflake is known for, but it also offers the advanced analytics and data science options through ClearScape Analytics,” Henschen added.
Snowflake seems to have just scratched the surface in terms of the depth and breadth of data science capabilities that companies need with its Snowpark offering and the recent addition of support for Python, Henschen said.
However, the analyst pointed out that VantageCloud Lake edition’s administrative self-service and auto scaling capabilities are the main draw for mid-sized companies and departments unsure of their analytical data platform needs.
“The administrative self-service and auto scaling capabilities are what drives customers to Snowflake. The new offering should make Teradata more competitive in that segment,” Henschen said.
VantageCLoud Lake is a lakehouse approach by Teradata
Teradata’s new offering could be a simple answer to the data lakehouse approach and competes with the likes of AWS Redshift Serverless, an auto-scaling version of the Redshift service introduced last year, and Google BigQuery, which has always been attractive to enterprises from an ease-of-administration and auto-scaling perspective, Tony Baer, principal analyst at DBInsight said.
The addition of ClearScape analytics in the Lake edition also provides support for AIOps across an enterprise though they remain free to use the tools and language of their choice, analysts pointed out.
“ClearScape analytics acts as a focal point for Teradata customers’ analytics efforts by providing data scientists and developers with additional functionality, including an expanded in-database analytics library and new ModelOps capabilities, that can be applied to data in the VantageCloud platform without needing to extract it into other tools and platforms,” said Aslett.
ClearScape Analytics has added another 50 functions to address time-series analysis and other complex workloads, said Sanjeev Mohan, principal analyst at SanjMo, adding that other companies such as Snowflake have added in-database ML capabilities this summer.
“ClearScape Analytics’ integration with well-known ML frameworks and products like Amazon SageMaker, Dataiku, H2O.ai, etc. will further increase the adoption of ML within organizations as it makes it easier to leverage existing investments in already-developed models and in current-state ML platforms,” Mohan said, adding that enterprise users, for example, can use Teradata plug-in for Dataiku, or APIs for Amazon to closely integrate models and data.
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