Teradata makes VantageCloud Lake available on Azure
By making its cloud-native platform natively available on Azure, the data management and analytics vendor aims to more smoothly enable users to run machine learning and BI tasks.
Teradata on Tuesday made VantageCloud Lake generally available on the Microsoft Azure platform in a move aimed at enabling joint customers to more easily manage and execute analytics and machine learning workloads.
Teradata is a longtime data management and analytics vendor.
First launched in August 2022, VantageCloud Lake is the cloud-native version of VantageCloud, the vendor's multi-cloud and hybrid data management platform.
In addition, Teradata offers ClearScape Analytics, a BI platform that enables users to work with their data in Teradata's database rather go through the extract, transform and load process each time they want to explore and analyze their data.
Azure, meanwhile, is Microsoft's public cloud computing platform.
Improved connectivity
In March, Teradata and Microsoft unveiled an integration between VantageCloud and Azure ML designed to enable users of both to better deploy and execute their analytics and machine learning models.
According to studies, most AI and ML models -- perhaps even more than 80% -- never make it into production. The integration, therefore, aimed to break down barriers that keep data isolated and simplify the model development process to help organizations more successfully create useful models.
The integration, however, did not include VantageCloud Lake and was only with Azure ML rather than the full Azure platform.
By making VantageCloud Lake -- including ClearScape Analytics -- available on Azure, joint VantageCloud Lake and Azure customers can now use the full capabilities of both platforms without having to move data back and forth between the two.
Of particular note, joint users can enhance Teradata's tools with Azure's generative AI and ML tools -- Microsoft is an investor in OpenAI and has significant integrations with ChatGPT and other OpenAI generative AI platforms. In addition they can now modernize Azure workloads and applications with VantageCloud Lake's own data science capabilities and cloud-native architecture.
As a result of the additive capabilities resulting from the combination of VantageCloud Lake and Azure, users of both platforms will benefit, according to Donald Farmer, founder and principal of TreeHive Strategy.
Making VantageCloud Lake available on Azure is not a development that will significantly alter what joint VantageCloud Lake and Azure customers can do with their data, but it is an incremental improvement, he noted. It portends that VantageCloud Lake -- which could run natively on AWS when it was made generally available -- will continue to be available on major cloud data platforms.
"It's a good move from Teradata to build stronger partnerships with the big cloud vendors and run natively on those platforms," Farmer said. "Expect more of these announcements to follow with the other platforms."
While joining VantageCloud Lake's tools with Azure's generative AI and ML capabilities is one major benefit of native connectivity between the two platforms, another is combining Teradata's advanced data science capabilities -- including governance -- with ML workloads in Azure.
It's a good move from Teradata to build stronger partnerships with the big cloud vendors and run natively on those platforms. Expect more of these announcements to follow with the other platforms.
Donald FarmerFounder and principal, TreeHive Strategy
Farmer noted that some of Azure's more advanced users may want more sophisticated capabilities than they get from Azure, and Teradata's are more modern.
"Teradata has deep and proven expertise in running complex workloads at scale with policy-driven governance and management," Farmer said. "So for anyone outgrowing their existing ML capabilities on Azure but with stringent governance needs -- think healthcare, pharmaceuticals, financial services -- this is a promising, but not surprising, move."
Mike Leone, an analyst at TechTarget's Enterprise Strategy Group, similarly said VantageCloud Lake's native availability on Azure will lead to improvement for joint customers.
"By bringing together ClearScape Analytics with Microsoft Azure ML, joint customers will be better empowered to experience end-to-end analytics pipeline and AI support," Leone said. "That includes generative AI. Organizations are seeking simplification and acceleration to jumpstart their AI. This partnership enhancement will deliver just that to joint customers."
Future plans
VantageCloud Enterprise is already available on AWS, Azure and Google Cloud. At the time VantageCloud Lake was unveiled with availability on AWS, Teradata chief product officer Hillary Ashton said the vendor planned to also make the cloud-native platform available on all three major clouds.
VantageCloud Lake's availability now on Azure leaves only Google Cloud remaining.
Beyond availability on multiple clouds, the vendor would be wise to address its cost and the ease with which new customers can get started with the vendor's tools, according to Farmer.
Teradata offers its Vantage platform at three different levels. All are consumption based, with Enterprise starting at $9,000 per month, Enterprise+ starting at $10,500 per month and Optimized Cloud at $31,000 per month.
Even the least expensive option amounts to a starting cost of more than $100,000 annually.
"Next for Teradata [should be to] enable faster, more cost-effective onboarding for new customers," Farmer said.
Leone, meanwhile, said Teradata's product development is on the right track, particularly related to infusing its Vantage platform with AI to improve business efficiency.
"I think they're focusing on the area where they need to in order to accelerate their market position the most, and that's on enabling businesses to go from data to decision as fast as possible with AI," he said.
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
