
The example runtimes shown above demonstrate the difference in performance that can be achieved utilizing fairly modern hardware. This also demonstrates the inbuilt parallelism supported by Oracle and Unix. This explains the performance difference for the first test (Oracle) with the second, as scrambling for 180 tables were submitted in parallel sets of 5 (this can be adjusted by the user).
The bottom test (100 million rows scrambled in 58 minutes) is the likely scenario of running against SQL Server on a equivalent multi-processor machine running Windows (i.e. no operating system parallelism employed, but using multi-processor parallelism).
Click here to read more about the Fast Data Masking™ architecture and technical information.
Masking, encrypting and de-identifying sensitive and personal data for use in non-production environments is quickly becoming a hot topic, as using "live" production data in development and testing is slowly becoming more and more unacceptable. Increased legislation, governing bodies like HIPAA, the PCI DSS and the GLBA, company fines, highly embarrassing data loss and data theft are forcing all companies to look at how they use production data for development and testing. In addition, the increased use of offshore, near shore and virtual images opens up all sorts of problems for securing your data from prying eyes.
Fast Data Masking™ for Oracle (FDM) is an easy to use, no hassle solution which allows you to mask, reduce, compress and reorganize your test data in one operation. Using a powerful array of data masking functions, seed tables and high performance techniques you will quickly be able to create legally compliant databases for testing and development.
FDM has an array of functionality to help you manage your large Oracle test databases.
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Requirement: Creation of data for load testing. As part of load testing on a desktop application, I was asked to insert data in three tables with 100, 1000 and 10, 000 rows.
Conventional way: A simple spreadsheet was used to populate the data by referring to the schema of the database objects. We populated dml statements in a spreadsheet and converted this to an SQL file and then executed the file. It took the effort of two resources for 1.5 days.
Datamaker: This can be done in few minutes by using Datamaker” Suresh Jetty, Quality Test Engineer, Satyam Services