Lowest cost for enterprise analytics

Teradata is Still the Lowest Cost for Enterprise Analytics

Tyler Owen
Tyler Owen
2022年7月14日 3 分で読める

Teradata provides the lowest cost per query for enterprise-scale analytics. Have your doubts? Please join me for a short read, the proof is in the pudding.

Many of today’s cloud database and analytics software vendors position their solutions as the end all be all and the cheapest option. Today’s reality is Enterprise customers have a robust and ever-growing list of requirements that isn’t easy to meet. Moreover, once analytics are operationalized the economic model can shift dramatically. In short, Enterprise customers need to look beyond basic data management and data sharing offers cobbled together with disparate tools. What is really needed is complete Enterprise Analytics Platform that delivers acceptable performance at the lowest cost. 

An Enterprise Analytics Platform starts by Integrating cross-functional data across all boundaries serving multiple applications and user groups across a wide ecosystem. At one end of the spectrum is the data scientist pulling data sources together looking for answers and at the other end, extreme concurrency. Consider running over 60 million queries per day or scoring models across millions of rows daily. The needs are dramatically different, but Teradata can do it all. From embedded data mining tools in an easy-to-use ecosystem to robust workload management capabilities Teradata delivers both and does it economically.  For the last several years Teradata has been extending the best-in-class analytics platform by providing the tools and ecosystem for the data scientist and providing the ability to operationalize it. This is where the rubber meets the road. Once analytics are operationalized and more users and applications are added, you can quickly see costs rise. If the software is not capable of meeting advanced requirements, you may be left with having to change the platform, which is extremely disruptive and limits the business value you can realize.


Customers are choosing Teradata because of the flexibility of Teradata’s Vantage platform. Teradata provides customers the ability to effectively move from a exploratory analytics to best in class enterprise analytics with no disruption. Vantage runs everywhere and is the leading advocate for moving processing to the edge instead of moving data to the processing.  

How does Teradata Vantage do both exploratory analytics and Enterprise Production economically? The answer is in the platform.  Customers can start with consumption pricing on the Cloud Service Provider of their choice. Paying for the processing and storage they actually use vs. what’s provisioned while exploring vastly different data sources across multiple platforms. When it’s time for operationalizing the analytics processing customers can seamlessly move the workload to a larger production instance and either retain consumption pricing or switch to a more traditional capacity pricing. Can all this be done effectively in the cloud, across clouds and on-premises? Absolutely, and Teradata is leading the charge.

In February this year Teradata demonstrated extreme analytic capabilities in the cloud running over 1,000 node test on AWS. Read Datanami’s coverage of the story here.

Bottom line. Inexpensive cloud only Data Warehouses may look great at the low-end during vendor crafted POCs, but in reality implementations can get very expensive if deployed at production scale. Some organizations have seen upwards of 3-7X higher costs than originally projected. This has forced some deployments to shift to different solutions mid-stream. Save time and money, with Teradata’s best in class analytics platform. 


会社情報 Tyler Owen

Tyler Owen is a software visionary focused on delivering solutions that solve real business challenges. At Teradata Tyler manages a team responsible for the global marketing of Teradata’s core products.  Tyler received his Master’s from Chapman University and resides in San Diego, California with his wife and two daughters.

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