Currently we offer a selection of tasks and data flow pipeline components which are available free of charge. These products have been developed to the highest professional standards and serve to illustrate our skills and experience of developing custom components for SQL Server Integration Services.
Whilst serving as examples of Component Design services we are sure you will find them useful additions to your toolbox. For some common questions and answers about these components see the Community Products FAQ .
The Checksum Transformation computes a hash value, the checksum, across one or more columns, returning the result in the Checksum output column. The transformation provides functionality similar to the T-SQL CHECKSUM function, but is encapsulated within SQL Server Integration Services, for use within the pipeline without code or a SQL Server connection. Checksums can reduce network contention and increase process performance by allowing you to verify data through a single value rather than transferring all data values for comparison.
This source component literally generates data. Specify how many columns you want, and how many rows, then watch the data flow out. Build demonstration and research scenarios faster with this simple source.
The File Watcher Task does what it says really, it watches a folder waiting for files. When an available file is found the task completes, returning the name of the file for onward use within the package.
The RegexClean Transformation is all about cleansing data using regular expressions by splitting, extracting and replacing tokens in your data within the pipeline. One or more columns can be selected, and match and replace expressions can be applied providing cleansed output data.
The Regular Expression Transformation exposes the power of regular expression matching within the pipeline. One or more columns can be selected, and for each column an individual expression can be applied. If all columns selected pass their tests then rows are passed down the successful match output. Rows that fail to pass all tests are directed down the alternate output.
The Row Count Plus Transformation can replace the stock transformation. We have recreated and extended with more functionality and a user friendly interface for faster and easier package design.
The Row Number Transformation calculates a row number for each row. It offers ROW_NUMBER or IDENTITY like behaviour within the Data Flow. Uses include surrogate key generation or data partitioning within the pipeline.
The Trash Destination Adapter is a development aid. It allows you to quickly terminate a data flow path, and does not require any configuration. It will consume the rows without any side effects, and prevents warnings or errors you may otherwise receive when executing the data flow.