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Materialized views that store data based on remote tables were also known as snapshots [5] (deprecated Oracle terminology). In any database management system following the relational model, a view is a virtual table representing the result of a database query. Whenever a query or an update addresses an ordinary view's virtual table, the DBMS ...
These features included the ability to define types and to fully describe relationships – something used widely, but maintained entirely by the user. In POSTGRES, the database understood relationships, and could retrieve information in related tables in a natural way using rules. POSTGRES used many of the ideas of Ingres, but not its code. [31]
For example, two tables, transaction_user and transaction_amount, would both contain the column "key", and keys between tables would match, making it easy to find both the user and the amount of a specific transaction if the key is known. This relational technology allowed people to correlate information stored in a primary table and its shadow.
Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.
Denormalization is a strategy used on a previously-normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
According to PostgreSQL v.9 documentation, an SQL window function "performs a calculation across a set of table rows that are somehow related to the current row", in a way similar to aggregate functions. [7] The name recalls signal processing window functions. A window function call always contains an OVER clause.
A master data recast is another form of data transformation where the entire database of data values is transformed or recast without extracting the data from the database. All data in a well designed database is directly or indirectly related to a limited set of master database tables by a network of foreign key constraints.
To process this statement without an index the database software must look at the last_name column on every row in the table (this is known as a full table scan). With an index the database simply follows the index data structure (typically a B-tree) until the Smith entry has been found; this is much less computationally expensive than a full ...