Fuzzy matching: what are the key differences between MS SQL and SAP DS?

[Former Member]

Hi Experts, I have a rather specific question, but maybe someone knows if not the complete answer, then at least the "guidelines". The question is as follows: what are the key differences between the implementation of fuzzy matching (lookup against reference data, grouping of input data) in MS SQL Server and SAP Data Services?

It would be most helpful if we could spot the major differences (or, on contrary, major similarities) along the following lines:

1) Composition and usage of ETI (Error-Tolerant Index) - is the composition and usage logic the same in MS SQL and SAP DS?

2) Tokenization of text strings, with further splitting into q-grams - is the usage of specific mathematical methods (clustering, etc.) the same?

3) Definition of token/q-gram subsets to be used in non-exhaustive matching - are the subset definition rules the same?

Any advice, experience sharing or thought would be precious.

Thanks,

Sergey

[Former Member]

Hi Sergey,

In what way you want to compare MS SQL Server and SAP DS?

MS SQL Server is a database and SAP DS is an ETL tool that can connect to a source, extract data, transform them and load it to a database/files/other target.

Thanks, Arun J.

[Former Member]

Hi Arun, I would like to compare them on how each of them implements fuzzy matching. In this light, the portions of both engines that are being compared are Fuzzy Lookup/Grouping (MS SQL Integration Services) and Data Quality Management (Data Services). Sorry if it was not clear from my initial post above...

Thanks.

Sergey