Data storage and analytics company Teradata may not have been born in the cloud, but it has certainly made a home there in recent years. Now, it’s looking to do some remodeling with artificial intelligence (AI).
This week Teradata struck a deal to integrate Google Cloud’s Vertex AI capabilities into its VantageCloud platform, supplementing earlier agreements with Amazon Web Services (AWS) and Microsoft Azure.
So, what the heck does it mean to “integrate” AI from the big cloud providers? Mike Riordan, senior director product management for data science and analytics at Teradata, told Silverlinings it starts with the creation of data sets within Vantage, which are then enhanced using its ClearScape Analytics feature engineering tools.
“These become the starting point of the data science work in Vertex AI to build high-quality AI/ML models,” he explained.
The API integration between VantageCloud and Vertex AI means once new models are created and made public, Teradata’s customers can leverage them using a Vantage query to glean new analytics insights.
Basically, the idea is to make it easier for Teradata customers to tap into the power of AI. Riordan said integrations like the one with Google Cloud are key because they eliminate “complexities with data transformation across diverse datasets,” ultimately saving “time and effort for data scientists” and allowing enterprises to “get more analytic value from their data.”
Teradata's bread and butter
The cloud hasn’t always been Teradata’s bread and butter – in part because it was founded in 1979, well before the cloud boom – but the medium was a natural fit for the company’s longtime focus on data warehousing and analytics.
Born from research conducted at the California Institute of Technology, Teradata was named for the ability to store terabytes of data. It first achieved profitability in 1986, went public in 1987 and was briefly owned by AT&T in the mid-1990s before becoming its own company once again in 2007.
It first launched Teradata Cloud, its analytics-as-a-service offering, in 2013. Three years later it made its Teradata Database service available on AWS and debuted a Hybrid Cloud product which allowed customers to deploy a combination of on-premises, managed cloud and public cloud resources for their data storage. Availability on Microsoft Azure and Google Cloud followed in 2017 and 2019, respectively.
Riordan said Teradata pivoted to a cloud-first strategy in 2020 and since that time the company’s cloud business has grown “sixfold.” While this obviously includes new business, Riordan noted “we’re also seeing an acceleration of existing Teradata customers moving to the cloud with us.”
Since 2020, Teradata has expanded its cloud offerings on AWS, Azure and Google Cloud, and in 2021 it inked a three-year strategic collaboration deal with AWS focused on facilitating cloud migrations.
Processing power
The company’s most recent moves, though, have homed in on enabling enterprises to apply AI processing power to the treasure troves of data it stores. These efforts specifically center on the aforementioned VantageCloud platform, which comprises data lake/warehouse and analytics services.
AWS was the first partner in Teradata’s AI push, with the pair inking a SageMaker integration deal in June 2022. Teradata followed up in March 2023 with a deal to make Azure’s machine learning capabilities accessible on VantageCloud. And its agreement with Google Cloud this week to integrate the cloud giant’s Vertex AI models rounds out the big three.
Among other Cloud Database Management Systems, Gartner in December ranked Teradata alongside Snowflake, SAP, Databricks, Alibaba Cloud, MongoDB, Cloudera and IBM in the lower half of its market leaderboard. The big guns in the space are exactly who you’d expect: AWS, Microsoft, Google and Oracle.
In terms of customers, Riordan said its base includes 17 of the top 20 global commercial and savings banks, eight of the top 10 U.S. retailers, nine of the top 10 global healthcare providers and 16 of the top 20 travel and transportation companies.
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