Office of Technology Transfer – University of Michigan

Cross-Vendor Database-Warehouse Compatibility Application

Technology #6558

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Researchers
Tyler Worman
Managed By
Drew Bennett
Associate Director - Software Licensing 734-615-4004

Big Data has seen a rapid adoption due to its promise to allow companies to embrace a predictive outlook on market modeling. This has rapidly created a US$3.2 Billion industry that is expected to continue growing at a CAGR of 25% over the coming years. The backbone of Big Data hinges on the ability to store vast amounts of information and process this information in a timely manner. These problems have been traditionally separately addressed, with databases serving the role as data-holder and data warehouses serving as advanced analytical tools. Due to the segmentation in the infrastructure and companies that offer these products, customers often require data to be translated between formats to fully utilize these technologies. The product presented here is designed to allow for seamless translation between Netezza data warehouses and Oracle Database storage systems. This translation is able to be run natively, within an application on a client computer, without the need for server implementation or additional hardware.

Free Migration Between Netezza and Oracle Database

The technology described here is a python based application, utilizing the TK interface, which allows for the scheduling and processing of data transfers between Oracle Databases and Netezza systems. This is accomplished by utilizing the ceODBC plugin for Python to communicate with both appliances in the ODBC format, using their respective drivers. The application is able to run entirely on the client machine and does not require being hosted on a server or access to its own data storage system for temporary file storage.

Applications

  • Transferring data between Oracle Database and Netezza
  • Synchronizing databases across Oracle and Netezza

Advantages

  • Small efficient program that offers streamlined experience
  • Able to be run locally on client machine or in hosted applications