Storage efficiency vs Random Access
Column data is of uniform type; therefore, there are some opportunities for storage size optimizations available in column oriented data that are not available in row oriented data. For example, many popular modern compression schemes, such as LZW, make use of the similarity of adjacent data to compress. While the same techniques may be used on row-oriented data, a typical implementation will achieve less effective results. Further, this behavior becomes more dramatic when a large percentage of adjacent column data is either the same or not-present, such as in a sparse column (similar to a sparse matrix). The opposing tradeoff is Random Access. Retrieving all data from a single row is more efficient when that data is located in a single location, such as in a row-oriented architecture. Further, the greater adjacent compression achieved, the more difficult random-access may become, as data might need to be uncompressed to be read.