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Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
In JavaScript, PHP, VBScript and a few other dynamically typed languages, the standard equality operator follows so-called loose typing, that is it evaluates to true even if two values are not equal and are of incompatible types, but can be coerced to each other by some set of language-specific rules, making the number 4 compare equal to the ...
Gadfly is a collection of Python modules that provides relational database functionality entirely implemented in Python. It supports a subset of the standard RDBMS Structured Query Language (SQL). [1] [2] Gadfly runs wherever Python runs and supports client/server on any platform that supports the standard Python socket interface.
Meanwhile, COALESCE simplifies the process of handling NULL values by returning the first non-NULL value in a given list of expressions, which is especially useful in scenarios where data might be incomplete or missing. Furthermore, SQL's support for three-valued logic (True, False, Unknown) introduces nuances when handling NULL values in ...
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
A comprehensive embedded domain-specific language for SQL in Python called "SQLAlchemy Core" that provides means to construct and execute SQL queries. A powerful ORM that allows the mapping of Python classes to database tables. Support for database schema migrations. Compatibility with multiple database backends.
The team released version 1 to a small number of users in June 1989, followed by version 2 with a re-written rules system in June 1990. Version 3, released in 1991, again re-wrote the rules system, and added support for multiple storage managers [32] and an improved query engine. By 1993, the number of users began to overwhelm the project with ...