Something more automatic?Edit2: This is what the complete query looks like, just in case it helps someone in the future. Talking about the speed of operation, a left outer JOIN is obviously not faster than an inner join.As per the definition, an outer join, be it the left or right, it has to perform all the work of an inner join along with the additional work null- extending the results. Robert Notwicz 2007-04-24: re: Better Alternatives to a FULL OUTER JOIN I have three tables, each of whose rows can be associated to any number of rows in the other two (through reference … To do this you could write two separate queries and provide two separate results, such as two spreadsheets, or you could use the UNION clause to deliver one result.In order to unite two tables there are a couple of requirements:When rows are combined duplicate rows are eliminated. EmpSalary table, it has returned NULL corresponding to those. Possible values are Inner Join, Left Outer Join, Right Outer Join, Full Outer Join, Left Semi Join, Left Anti Semi Join, Right Semi Join, Right Anti Semi Join, Concatenation, and Union. SELECT COALESCE(T1.Col1,T2.Col1) As Col1, COALESCE(T1.Col2,T2.Col2) As Col2 FROM T1 FULL OUTER JOIN T2 ON T1.ID = T2.ID Matches on ID to combine rows. Hence, when you ask which join to use, you are actually asking whether to write aa. He loves helping others learn SQL. Then: Thanks for the feedback! Stack Overflow works best with JavaScript enabled This is a default join in Access and the most frequently used one too. Tip: FULL OUTER JOIN and FULL JOIN are the same. Your cross join isn't a FULL OUTER JOIN at all. In this statement, the column_list_1 and column_list_2 must have the same number of columns presented in the same order. A most common example is the join between two tables through the primary key column and foreign key column.Suppose, we have got a table which contains employee Salary and there is another table which contains employee details.In this case, there will be a common column like employee ID which will join these two tables. The result of UNION includes the tuples from both the relations present in the query.