Last summer, in the run up to launching Teradata VantageCloud Lake, our Products Team was singularly obsessed with one thing and one thing only – launching a new cloud-native product that leapt ahead of the competition, delivering THE platform for AI and ML from start to scale to the market and our customers.
Looking back, I barely remember the individual days, but will always remember that time. Every ounce of our creative and technical energy was being poured into every detail that made up Vantage Cloud Lake. Every step forward was exhilarating, and every setback was a collective lesson we took forward. I cannot remember a time in my career that was more intense or more fun. In the midst of all of our hard work we did a 1,000-node test demonstrating that enterprise customers can run their complex analytic workloads on a single system in the cloud at unprecedented scale. This largest single-system cloud deployment proved that we 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.
So now, almost a year later, we’ve done it again! Just like any maker-team that endeavors to put the best product possible into the world, we focus relentlessly on new capabilities to delight our customers.
We've opened VantageCloud Lake to customers in new markets with bleeding-edge ClearScape Analytics so that they can derive even more value as they innovate and create new opportunities faster than ever before. We used to think running hundreds of models in seconds was impressive, but now customers can run thousands (and hundreds of thousands) of Generative AI, AI, and ML models, in-database, at record speed and scale. And, with the help of our partners, Microsoft Azure and Amazon Web Services, we make it all happen in the cloud. Extending the endless possibilities together gives customers the confidence to take big risks for big payoffs!
We might turn this headline into a sign and hang it in the office:
Continuous Innovation Lands Teradata as the Gartner Leader Again
The real beauty in that statement is what it means for our customers – the real stars of the show and why working like mad scientists is so fun.
Our customers can now do the very thing that better enables them to thrive as a business – use their data (wherever it lives) to make decisions. That superpower earned Teradata a continued leadership position in the Gartner Cloud Magic Quadrant and (drum roll) a #1 ranking in all four use cases of the Gartner Critical Capabilities for Cloud Database Management Systems reports. Mic drop.
We have always invested our tech chops, time, and resources into analytics and data management. Now, our complete cloud analytics and data platform, VantageCloud Lake, enables businesses to deliver harmonized data, enrich customer experiences and improve business performance.
VantageCloud Lake inherits Teradata’s rich innovative technology that enabled us to maintain a leadership position in the Magic Quadrant, and the #1 position in all four use cases of Gartner’s Critical Capabilities report.
Let’s dig a little deeper into each key capability and examine how VantageCloud Lake continues to raise the bar thwarting the competition.
- Traditional Data Warehouse
- Logical Data Warehouse
- Data Lake
- Streaming Analytic
Traditional Data Warehouse
Teradata scored 4.71 (scale 0-5) where there were only 2 other vendors that scored a 4 or better. Gartner heavily weighs (20%) “resource usage” as a key criterion in this use case. In Teradata speak, resource usage equates to workload management where Teradata has far more extensive capabilities than any other vendor. Per Gartner, “Teradata Vantage can run mixed workloads of operational style queries, as well as heavy analytical workloads, and can do so reliably at high scaling factors.” VantageCloud Lake benefits from Teradata’s workload management capabilities and goes beyond optimizing a single pool of resources by enabling customers to isolate workloads as well. Leveraging and building on Teradata’s key strengths, VantageCloud Lake enhances overall resource management.
The next 2 critical criteria are “relational attributes” (15%) and “financial governance” (15%). Teradata was the only vendor to get a perfect score for relationship attributes, indicating Teradata’s ability to support complex queries across many tables that other vendors simply can’t. Included in this ranking are the strengths of Teradata’s Industry leading Optimizer, and the extensive nature of our SQL support and capabilities enabling true differentiation with ClearScape Analytics. Teradata is the only vendor that can process the most extensive suite of in-database analytics with performance and scale.
For financial governance, Teradata tied for the top score. VantageCloud Lake has built-in differentiation to allow customers to govern better by optimizing spend management. VantageCloud Lake’s smart scaling is designed to provide guardrails for organizations to stay within budget. Coupled with real time telemetry data presented in the Console, Lake lets organizations monitor and control resource consumption for optimized financial governance at a macro level.
Based on the top 3 weighted criteria, you can see how Teradata earned the top spot for the Data Warehouse critical use case. With VantageCloud Lake, and its ability to provide workload isolation in addition to workload management, continued inherent relational attributes stemming from the Analytics Database, and a strong emphasis on financial governance, the differentiation that drives Teradata as the best-in-class solution supports Teradata’s current and future leadership position.
Logical Data Warehouse
In the Logical Data Warehouse use case, Teradata scored 4.85 out of 5; the next closest vendor scored 4.16, almost a full point gap in our differentiation. The “distributed capabilities” criterion is the most heavily weighted criteria at 40% of the total ranking and Teradata is the only vendor to get a perfect score. Teradata QueryGrid provides an orchestrated heterogeneous data fabric that enables push down processing and minimizes data movement. As an intelligent cross-platform technology supporting distributed capabilities, QueryGrid supports multi-cloud and hybrid deployment options, another Teradata differentiator that is separately weighted and contributes an additional 10% to the Gartner ranking. With VantageCloud Lake, we’ll be expanding connectivity to additional data sources. Plus, our Native Object Store (NOS) capability provides access to object store data across platforms, both on-prem and in multiple clouds. Per Gartner, “Teradata’s scores are supported by its strong distributed access, data sharing and data placement features ...This positions Teradata well as an enabling hub for multiple analytical systems.” Teradata’s goal is to be at the center of data access, serving as an enabling hub for multiple analytical systems. Already a leader, Teradata’s robust roadmap, including support for Apache Iceberg, Apache Hudi, and Delta Lake, will further differentiate VantageCloud Lake as a supporting technology and maintain a leadership position.
Data Lake
The Data Lake use case has an expanded definition from years past that includes the storage and processing of data of all different structures, specifically focusing on data engineering, data science and other use cases, at scale. Teradata scored 4.25 and only 3 other vendors scored a 4 or better. The highest weighted criteria are “data science” (35%). VantageCloud Lake inherently shines in this use case as it includes ClearScape Analytics as part of the solution and it supports multiple data structures (NOS, JSON, XML). ClearScape Analytics features broad accessibility and ease of implementation to accelerate value with greater AI/ML adoption. Automated optimization of model operations rolls out continuous improvements while costs are managed effectively, resulting in the greater return on investment and sustainable value driven only by AI/ML at scale. As industry analyst Tony Baer notes “Teradata is finally drawing attention to the fact that it is a holistic analytics platform and not simply a data warehouse, data lake or lake house. Teradata’s differentiation goes beyond the optimized SQL engine and infrastructure to include analytics optimized for that engine. The launch of VantageCloud Lake is the beginning of a new journey for Teradata and our customers.”
Streaming Analytics
Lastly, the “Streaming Analytics” use case focuses on analyzing streaming data as it enters the system with the top two criteria, each at 25%, as “analytics on streaming data” and “streaming optimization.” Teradata scored 4.25 and only 1 other vendor scored a 4 or better. With top scores on both criteria, Teradata’s long history of ingesting near real-time data provides significant advantages over the competition. Along with interfaces to multiple streaming services, Teradata continues to invest in streaming capabilities for both data ingest and for analytic processing. Lake provides these streaming capabilities with a new continuous Data Flow feature that enables automated continuous loads from cloud-native object storage.
Net Net
Teradata’s top scores in all 4 analytical use cases of the Gartner Critical Capabilities for Cloud Database Management are based on years of continuous innovation across the Teradata Vantage Analytics and Data Platform.
With VantageCloud Lake and ClearScape Analytics, we are confident in our ability to maintain our #1 ranking and we are excited to deliver even more innovation to our customers in our exciting roadmap.
Teradata’s focus on innovation is embedded in our platform evolution and our DNA. The Vantage Analytics and Data Platform provides flexibility and agility -- adjusting and adapting to any or all of these use cases.
The Good News
Customers continue to rely on Teradata Vantage across deployment options and design patterns. The work-horse for data warehouses, data marts, and data lakes, both on-prem and in the cloud, extensibility is engineered into the platform. Design patterns and use cases change over time. Customer platforms don’t need to.
