SQL Query Translation Layer for Database Interoperability
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Solution Overview
Problem
The implementation of SQL code is not completely interchangeable among different database systems due to proprietary extensions, causing issues when transitioning from one database to another.
Innovation Solution
A system and method that maps standard SQL statements to query statements suitable for a target database by parsing and transforming them into an Abstract Syntax Tree (AST) representation, adding properties and annotations, and unparsing them into the appropriate SQL statements for the target database, using a statement mapping database to manage and translate between different SQL dialects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standard SQL statements are used across different database systems, then interoperability and ease of operation are improved, but compatibility and reliability deteriorate due to proprietary extensions
Solution Approach 1:
The patent implements a translation layer that acts as an intermediary between standard SQL statements and target database-specific SQL statements. This translation layer parses the standard SQL, transforms it into the appropriate dialect for the target database, and handles proprietary extensions, thereby maintaining both interoperability and compatibility simultaneously.
Solution Approach 2:
The system dynamically changes the parameters of SQL statements based on the target database system. By detecting the target database type and adjusting the SQL syntax, functions, and parameters accordingly, the system maintains compatibility with proprietary extensions while accepting standard SQL as input, thus resolving the contradiction between ease of operation and reliability.
2Adaptability or versatility
If database vendors add proprietary extensions to enhance functionality, then adaptability and versatility are improved, but device complexity and difficulty of operation worsen
Solution Approach 1:
The patent segments the SQL processing into distinct components: a parser for standard SQL, a translation engine, and a target-specific execution layer. This segmentation allows the system to handle proprietary extensions in a modular fashion, managing complexity by separating concerns while maintaining enhanced functionality through targeted extensions in the translation layer.
Solution Approach 2:
The translation layer serves as an intermediary that absorbs the complexity of proprietary extensions. It translates between standard SQL and database-specific extensions, allowing users to work with simple standard SQL while the intermediary handles the complex translation to support enhanced functionality and adaptability.
3Adaptability or versatility
If database vendors add proprietary extensions to enhance functionality, then adaptability is improved, but ease of operation worsens when transitioning between databases
Solution Approach 1:
The translation layer acts as an intermediary that automatically handles the transition between different database dialects. Users write standard SQL and the intermediary translates it to the appropriate target database syntax, eliminating the need for manual adaptation and maintaining ease of operation during database transitions while supporting proprietary extensions.
Solution Approach 2:
The system performs preliminary translation of SQL statements before execution on the target database. By pre-processing the SQL to account for proprietary extensions and dialect-specific requirements, the system prepares the statements in advance, making the transition between databases seamless and maintaining ease of operation.
Data Source
AI summary
A system and method for mapping a standard set of database query statements to a set of query statements for a target database, including a processor to receive an identification of a target database and identify any extension set of query statements of the target database, receive a plurality of standard database query statements, and map each standard database query statement to a query statement for the target database on the basis of an extension set associated with the target database. A statement mapping database may be created to map the query statements of the target database to the standard database query statements such that the processor may receive a standard database query statement and identify a corresponding query statement that is appropriate for the target database, and receive a query statement of the target database and identify a corresponding standard database query statement.