Teradata’s top 10 innovations in 2022

As we start 2023, our product marketing team has compiled a list of the top 10 features in Teradata Vantage which have immensely helped our customers and are technological breakthroughs.

Pranay Dave
Pranay Dave
January 6, 2023 7 min read
Teradata's top innovations in 2022

Welcome to our blog on the top 10 Teradata Vantage product features for the year 2022! As we start 2023, our product marketing team has compiled a list of the top 10 features in Teradata Vantage which have immensely helped our customers and are technological breakthroughs.    

Whether you're looking to stay up to date on the latest and greatest or just want to stay ahead of the curve, this blog is for you. So, sit back, relax, and get ready to find out about exciting things which Teradata delivered in 2022! 

10. Teradata 1000 node test 

Teradata announced the results of one of the largest-scale cloud analytic tests ever undertaken in the industry. Its success demonstrates that enterprise customers can run their complex analytic workloads on a single system in the cloud at an unprecedented scale. 

Modern data platforms in global 3,000 organizations often support tens of thousands of users and thousands of mission-critical business applications. This activity level drives upwards of 100 million queries-per-day, executed against petabytes of continuously updated data. 

With the success of its recent scale test, Teradata proved that it can successfully operationalize analytics at scale (1) on a single system of more than 1,000 nodes with (2) 1,023 active users submitting thousands of concurrent queries, (3) using a diverse set of mixed workloads, (4) and with no system downtime or outages. 

9. Unbounded Array Framework (UAF) 

Our innovative new way to operationalize analytics has now arrived with our Unbounded Array Framework and is available with Vantage. 

With this new framework, we are making massive improvements in scalability for in-database functions. Unbounded array framework is more performant compared to other analytic frameworks, such as Python/R or SQLMR. 

This is unique in the industry, and it will help you to operationalize analytics at hyper-scale. 

8. In-database time series functions for machine learning 

This year we also introduced 50+ time series in-database functions for machine learning.  These new time series functions can be leveraged to create end-to-end machine learning pipelines for time series data in a very scalable way.  

These functions are built on the Unbounded Array Framework and are highly scalable. You can use them to solve complex use cases such as retail forecasting on millions of products or time-series based anomaly detection on billions of IoT sensor data 

7. Enhanced partner integration with AWS, Azure, and Dataiku 

This year, we strengthened our integration with AWSDataiku, and others allowing data scientists to seamlessly work between Vantage and partner tools. 

Data scientists can prepare training data in Teradata Vantage leveraging in-database analytics capabilities, transfer the prepared data to partner tools for model training.  Once the model is created, they can be deployed as endpoints, users can score the model in Vantage via an API request through a user query.  

Alternatively, data scientists can also leverage the BYOM capabilities to deploy the model directly in Vantage. 

6. ModelOps 

The year 2022, will also be known as the year where we introduced breakthrough Teradata ModelOps which will allow manage and monitor machine learning models. With ubiquitous machine learning on the rise, there will be more and more AI/ML models. With Teradata Vantage scalable database, you can store millions of AI/ML models and use model-ops to manage and monitor them. 

Teradata Vantage model-ops also include capabilities such as auditing datasets, code tracking, model approval workflows, monitoring model performance as well as alerting when models become non-performing.  

ModelOps can be leveraged to schedule model retraining as we drive towards autonomous retraining based on data drifts. ModelOps can manage and monitor models which are developed  using Vantage in-database analytics as well as those developed using open-source Python/R and partner models imported to Vantage using the BYOM approach.This ensures that all models are managed and monitored centrally irrespective of the technology which was used to produce them. 

5. Open Analytics Framework  

Open Analytics Framework allows data scientist to run Python/R on Teradata VantageCloud Lake and takes full advantage of the Lake architecture. Open Analytic Framework extends Teradata's current Script Table Operator (STO) capability by providing greater scalability, workload isolation, and library/code flexibility.  

Open Analytics Framework in the cloud leverages a serverless architecture that enables auto-scaling and consumption pricing.  

With Open Analytics Framework, Vantage becomes truly an open platform for executing a wide variety of advanced analytics. 

4. New unit-based pricing 

This year in 2023, we are bringing to market something that really responded to the business challenges that our customers were telling us about. They really wanted to be able to have a much more cloud native type pricing. They wanted to reduce their IT costs, and be able to control their budget without surprises. They wanted to better manage the resources that were available. They wanted to be able to do better reporting and allocation of costs across compute that they were experiencing and they wanted real-time visibility into that resource utilization. They wanted to be able to see what was happening. 

So Teradata listened to our customers and we came out with a pricing model that solves all of these challenges. The first version of that is on our enterprise vantage Cloud, enterprise unit pricing. And on this model, you truly pay only for what you use. We use a simple unit-based consumption model. Units work across either environment – VantageCloud Enterprise or VantageCloud Lake. And you truly only pay for the data that you access and that you compute, you actually burn. 

So as we roll into 2023, both these pricing packages will be available for our customer base introduced in 2022. It is going to be available in 2023. 

3. Vantage console for VantageCloud Enterprise 

Another significant milestone this year was the introduction of Vantage console for VantageCloud Enterprise. This new point of entry consolidates the diverse capabilities of Vantage into a unified console and provides many new self-service capabilities to empower everyone in your organization. From the database administrators to the data science teams, providing faster access, better governance and more powerful analytics at scale to support business goals. The key feature of Vantage console is the self-service active management capabilities. 

That enables specifically administrators and operators to easily monitor, manage, and scale instances of vantage across multiple cloud service providers. You can drill down to see all the details at a glance. 

Additionally, new cloud data protection functionalities added in help guard against both infrastructure failure and user error, including self-service creation and the whole life cycle management of backup as a service and disaster recovery as a service. 

Beyond the management tools Vantage console has also built-in, simpler and more comprehensive tools to empower data science teams to effortlessly explore and analyze data by doing more data search, share and explore all from one unified interface to maximize value and support key business goals. You can access Vantage console today at

2. ClearScape Analytics 

A significant milestone this year was the introduction of ClearScape Analytics, is the name for Teradata’s analytics capabilities available as part of the Teradata Vantage platform, including Teradata VantageCloud, Teradata VantageCore, and deployments within those offerings.  

With ClearScape Analytics, you can unlock the business value of AI. 

AI is a top tech trend of 2022, both in terms of investment as well as the global impact it can create for companies. It can lead to doubling the profits if used correctly. However, despite the high levels of interest in AI/ML, only a few companies have successfully adopted and scaled AI. 

The main challenges are related to the productivity of data, data science teams and transitioning from pilot projects to production.  

With ClearScape Analytics you can overcome these challenges. ClearScape Analytics consist of 

In-database analytics, with which you can solve complex analytics problems with zero data movement. In-database analytics will help you accelerate your data preparation as well as help you scale from a few models to millions of models. 

Open and connected analytics can help data scientists can leverage the power of massively parallel processing with open source or partner tools. This can help operationalize models developed with data scientists, preferred tools of choice and thus leading to faster time to value. 

Deploy AI models at scale by integrating them with operational data to make models actionable as well as monitor them with an automated process. Teradata Vantage platform also has the lowest TCO which will help you scale without cost overruns. 

1. Teradata VantageCloud Lake 

Teradata VantageCloud Lake was our big launch for this year. Teradata VantageCloud Lake leverages a next-generation cloud-native architecture. It provides lakehouse deployment patterns along with the ability to run independent elastic workloads using an object store-centric design. With VantageCloud Lake, all parts of a business can run analytics projects at will while sharing data in cost-effective object storage. Find out how organizations can now enable users to meet the increasingly diverse analytics and data needs of their evolving business. 

With the massive amounts of digital exhaust being generated today, many organizations are looking for a flexible, low-cost strategy to modernize their data ecosystems. Teradata VantageCloud Lake enables users to meet the increasingly diverse analytics and data needs of evolving business, expanding beyond enterprise workloads to meet departmental, exploratory, and ad hoc use cases. By leveraging a next-generation cloud-native architecture, VantageCloud Lake provides lakehouse deployment patterns with the ability to run independent elastic workloads leveraging an object store-centric design. This means all parts of a business can now run analytics projects at-will, while sharing data in cost-effective object storage.

And one more thing...

Teradata has once again been recognized as a Leader in the 2022 Gartner Magic Quadrant for Cloud Database Management Systems (DBMS). That’s an impressive 20 years in a row of being named a Leader in data analytics—we’re honored! 

Hope you enjoyed the blog. The Teradata product marketing team wishes you a great start to the new year. See you soon for another exciting year of technological breakthroughs and innovation!


About Pranay Dave

Pranay is Director for Product Marketing at Teradata. In this role, he helps customers and prospects understand Teradata's value proposition. Combing strong technical data science and data analytic skills, he participates in technology evangelisation initiatives.

In this global role, he participates in developing market strategy that drives product development delivering transformational value. Earlier he has worked as Principal Data Scientist enabling customers to realize business benefits using advanced analytics and data science. As a recognized expert in Teradata Vantage, Pranay is also a regular speaker at Teradata internal and external events. He is recognized as a top writer for AI in digital media. Pranay has degree in Data Science, MBA and Computer Engineering.

View all posts by Pranay Dave

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