Scaling Business Intelligence in the Cloud | Use Case

bank iconFORTUNE 100 Financial Institution

Executive Summary

A Fortune 100 Global Financial Institution needed to scale their business intelligence application, which was built using 2000-plus Teradata Stored Procedures. After multiple failed attempts, the customer’s own six-month analysis showed that replacing their Teradata footprint was prohibitively expensive, and rewriting the business applications to a more cost-effective and modern data warehouse posed significant expense and business risk. Datometry was able to successfully replatform all the stored procedures to Pivotal Greenplum Data Warehouse, and helped the customer develop a three-month roadmap for a cost-effective expansion of business intelligence.


The customer was dealing with the following challenges in scaling their Teradata business intelligence Stored Procedures:

  • CAPEX and OPEX for their current Teradata data warehouse were far too high.
  • After a six-month analysis on the feasibility of migrating the Teradata Stored Procedures to a more cost-effective data warehouse, they found that the high cost of rewriting the applications posed significant expense and business risk. The replatforming effort via rewriting the applications was a no-go decision.

Datometry’s Solution

  • Datometry® Hyper-Q™ functionality allowed the customer to transfer the stored procedures in days, rather than years, to the modern Greenplum data warehouse (GPDB).
  • Hyper-Q’s emulation of stored procedures enabled running procedures that GPDB did not support natively. Without Hyper-Q, the customer would have had to completely refactor the logic of the application and implement various control-flow primitives, a very time-consuming and expensive proposition.
  • Datometry helped create a three-month roadmap for deployment which included a hardening phase.

Why the Data Architect Chose Datometry

Enabled Business-Critical Proprietary Middleware to Connect to Modern Database

Hyper-Q enabled the customer to connect to a modern database without rewriting critical proprietary middleware.

Support for Stored Procedures

Hyper-Q enables running of stored procedures instantly and natively on the target data warehouse without being limited by the feature set of the new target data warehouse.

High Concurrency & Workload Management Capabilities

Hyper-Q supports high concurrency and workload management capabilities in mixed workloads.

Fast Deployment & Simple Implementation

Hyper-Q can be deployed instantly and requires a testing phase of just weeks. The software does not require tuning and provides complete visibility into its operations.

Why the Business Chose Datometry

Competitive Advantage

Hyper-Q enabled the customer to increase their business advantage derived from proprietary middleware by quickly and easily transitioning to a modern, more cost-effective data warehouse.

Preserve Business Investment

Hyper-Q does not require the rewriting of applications—typically a long, expensive, and risk-laden process for enterprises—thus allowing the customer to protect their long-standing investments in the development of proprietary business logic.

Accelerated Time to Value

Using Datometry Hyper-Q, the customer was able to significantly reduce the cost and time of replatforming their data warehouse.

Decreased Risk

Hyper-Q leaves existing applications unchanged which means projects can be fully tested in advance.

Datometry Adaptive Data Virtualization Technology

Datometry’s first-of-its-kind Adaptive Data Virtualization™ technology enables enterprises to run instantly and manage applications in cloud databases or data warehouses, within multiple databases or data warehouses, in the cloud, or between different cloud platforms. What this means for the enterprise is that business applications do not need to be rewritten or reconfigured, but can directly talk to Datometry Hyper-Q as if it were the original database or data warehouse. For example, applications originally developed for Teradata can now run transparently on Microsoft SQL DW, Amazon Redshift, Pivotal Greenplum, and other data warehouses.

Learn more about product features, platform overview, and read answers to many frequently asked questions at the Hyper-Q product page.

Sponsored by Datometry

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