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Sybase Integrates RAP With R Stat Programming Language

Now an SAP company after what appears to have been a comparatively painless acquisition last year, Sybase continues to target the financial sector with its Sybase RAP — The Trading Edition product. This analytics server for the "capital markets" sector has been enhanced with support for the R statistical programming language. The concept here is to provide the R language alongside Sybase RAP for faster algorithm development and extensive backward testing on historical data.

Targeting developers and data analytics specialists with this new integration, the company says that it is providing users with a means of analyzing large, complex datasets. The integration enables users to leverage functions in R packages within RAP using SQL. R users, in turn, are able to develop models by storing vast amounts of historical data for analysis and preprocessing using RAP. In essence, what Sybase has tried to achieve here is two complementary analytical, risk management ,and complex data-processing assets in one platform.

"R is an increasingly popular analytical package in capital markets, providing risk managers and quant traders with deeper analytics to help make better decisions," said Neil McGovern, director of financial services product management at Sybase. "Through interoperability with R, we are further enhancing the value of RAP to support the most demanding analytics requirements in capital markets via a single platform."

With the latest release of Sybase RAP, users can access functions running on an R server, via the RAPStore user-defined functions (UDF) capability, and invoke them as SQL functions within RAP. R customers can use the RJDBC package to access data on the RAPStore. By preprocessing on the RAP server, users can download the relevant subset of data and use it in their applications without having to download all the data and do the preprocessing in R, resulting in faster algorithm development. Additionally, they can also access large historical datasets in RAP for algorithm development and more accurate back-testing.

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