You can use data types with the following features to improve efficiency:
Generally, the calculation of integers (including common comparison calculations, such as =, >, <, ≥, ≤, and ≠ and GROUP BY) is more efficient than that of strings and floating point numbers. For example, if you need to perform a point query on a column-store table whose NUMERIC column is used as a filter criterion, the query will take over 10 seconds. If you change the data type from NUMERIC to INT, the query takes only about 1.8 seconds.
Data types with short length reduce both the data file size and the memory used for computing, improving the I/O and computing performance. For example, use SMALLINT instead of INT, and INT instead of BIGINT.
You are advised to use the same data type for a join. To join columns with different data types, the database needs to convert them to the same type, which leads to additional performance overheads.