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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.
SQL Server Compact is an embedded database by Microsoft with wide variety of features like multi-process connections, T-SQL, ADO.NET Sync Services to sync with any back-end database, Merge Replication with SQL Server, Programming API: LINQ to SQL, LINQ to Entities, ADO.NET. The product runs on both Desktop and Mobile Windows platforms.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
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/T-SQL, R, Python: Offers graph database abilities to model many-to-many relationships. The graph relationships are integrated into Transact-SQL, and use SQL Server as the foundational database management system. [34] NebulaGraph: 3.7.0: 2024-03: Open Source Edition is under Apache 2.0, Common Clause 1.0: C++, Go, Java, Python
[dubious – discuss] Inversely, a language may be designed for general use but only applied in a specific area in practice. [3] A programming language that is well suited for a problem, whether it be general-purpose language or DSL, should minimize the level of detail required while still being expressive enough in the problem domain. [ 4 ]
The SQL market referred to this as static SQL, versus dynamic SQL which could be changed at any time, like the command-line interfaces that shipped with almost all SQL systems, or a programming interface that left the SQL as plain text until it was called. Dynamic SQL systems became a major focus for SQL vendors during the 1980s.
In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query. For each table added to a SQL Query, one additional INNER JOIN is added to prevent a cartesian product. Thus, for N tables in an SQL query, there must be N−1 INNER JOINS to prevent a cartesian product.