If you would like to compare their contents perhaps this may help.
Write a select statement containing the fields for which you would like to compare data for, you may want to leave out fields whose values are provided by default for example fields populated from sequence object and/or timestamp fields.
You may need to include triming of leading and trailing empty spaces for the text based fields if such white spaces are not relevant for your defination of similarity.
The same may apply on rounding and formatting numeric data for example 9.900 could be equivalent to 9.9 in the other table based on your application of the data.
Include an ORDER BY clause to ensure you get the records in a predictable order.
Output these data to a CSV file without the CSV header.
Now rewrite the same query for the other table, this is required if the table definations are not common between the two tables.
Remember to substitute the table name accordingly.
Output these data to another CSV file without the CSV header.
Now run sha1sum on the first file and compare the returned sha1sum value with the value returned on running sha1sum with the second file.
Perhaps use "diff" tool.
Allan.
