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Additionally there is a single-row version, UPDATE OR INSERT INTO tablename (columns) VALUES (values) [MATCHING (columns)], but the latter does not give you the option to take different actions on insert versus update (e.g. setting a new sequence value only for new rows, not for existing ones.)
Tables whose changes must be captured may have a column that represents the time of last change. Names such as LAST_UPDATE, LAST_MODIFIED, etc. are common. Any row in any table that has a timestamp in that column that is more recent than the last time data was captured is considered to have changed.
A new dimension row is added with the new state of the source system; a new surrogate key is assigned; source key is no longer unique in the lookup table Fully logged A new dimension row is added with the new state of the source system, while the previous dimension row is updated to reflect it is no longer active and time of deactivation.
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
Max table size Max row size Max columns per row Max Blob/Clob size Max CHAR size Max NUMBER size Min DATE value Max DATE value Max column name size Informix Dynamic Server: ≈0.5 YB 12: ≈0,5YB 12: 32,765 bytes (exclusive of large objects) 32,765 4 TB 32,765 14: 10 125 13: 01/01/0001 10: 12/31/9999 128 bytes Ingres: Unlimited Unlimited 256 KB ...
A transactional table is the most basic and fundamental. The grain associated with a transactional fact table is usually specified as "one row per line in a transaction", e.g., every line on a receipt. Typically a transactional fact table holds data of the most detailed level, causing it to have a great number of dimensions associated with it.
A distributed database is a database in which data is stored across different physical locations. [1] It may be stored in multiple computers located in the same physical location (e.g. a data centre); or maybe dispersed over a network of interconnected computers.