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SQLAlchemy is an open-source Python library that provides an SQL toolkit (called "SQLAlchemy Core") and an Object Relational Mapper (ORM) for database interactions. It allows developers to work with databases using Python objects, enabling efficient and flexible database access.
C/C++, Python, R, Java, Go, Rust, Node.js, Wasm, ODBC, ADBC, and more [2] Open source (MIT License) DuckDB is an in-process database system designed for high performance for analytical query workloads offers client APIs for a wide range of languages. Exasol: Exasol AG 2000 JDBC, ODBC, ADO.NET, Python, SQL, R, Go, Rest API [3] Proprietary
A common criticism is that SQLite's type system lacks the data integrity mechanism provided by statically typed columns, although it can be emulated with constraints like CHECK (typeof (x) = 'integer'). [10] Strict tables were added in version 3.37.1. [22] Tables normally include a hidden rowid index column, which gives faster access. [24]
In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]
In relational databases, the information schema (information_schema) is an ANSI-standard set of read-only views that provide information about all of the tables, views, columns, and procedures in a database. [1] It can be used as a source of the information that some databases make available through non-standard commands, such as:
In relational databases a virtual column is a table column whose value(s) is automatically computed using other columns values, or another deterministic expression. Virtual columns are defined of SQL:2003 as Generated Column, [1] and are only implemented by some DBMSs, like MariaDB, SQL Server, Oracle, PostgreSQL, SQLite and Firebird (database server) (COMPUTED BY syntax).
[3] [better source needed] A column can also be called an attribute. Each row would provide a data value for each column and would then be understood as a single structured data value. For example, a database that represents company contact information might have the following columns: ID, Company Name, Address Line 1, Address Line 2, City, and ...
The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the result set.