As mentioned earlier, data resembling a table can be stored in linear memory either column by column, i.e. columnar layout, or row by row, i.e. row layout. The impacts have already been discussed in Chap. 8 in more detail. The columnar layout is optimized for analytical set-based operations that work on many rows but for a notably smaller subset of all columns of data. The row layout shows a better performance for select operations on few single tuples. In this chapter, we discuss the operations needed for tuple reconstruction in detail and explain the influence of the different layouts on the performance of these operations. Tuple reconstruction is a typical functionality in OLTP applications. It is executed whenever more than one column is requested from the database, for example when the user in an ERP system calls the “show” or “edit” transactions for the master data object or for a document.