This is a simple example of differencing SQL Server (right side) and Oracle (left side) data sets. Observe in the central portion of the that row differences are highlighted, and within those, column differences. The data in both grids originated from the respective queries at the bottom. Both queries call for an IDCountry
field but because ID values are different between systems, the IDCountry
field is ignored (data in that column is italicized and lightened). The name and code for the countries are the data we want to compare. Because they exist with different field names in the two databases, one side is aliased to use the same names as the other, allowing SqlDiffFramework to recognize they should be compared.
The results toolbar at the top right reports the key quantifiable difference measures: a 93% match overall, highlighted in the figure as point 1. The differences in this case are in three clusters (point 2) and the screen shot happens to indicate that the current difference cluster is the last of the three. The results toolbar further indicates that among the collective set of differences, there are 2 rows added to the left side that are not on the right side (point 3) and 5 rows that exist on both sides but contain different data (point 4).