Virtual Database Layer for Flexible Data Traversal
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Solution Overview
Problem
Users without extensive training in database management struggle to modify and extend relational databases due to the complexity of maintaining database structures, leading to potential errors in data access and functionality.
Innovation Solution
Implementing a method that uses attribute tables to determine paths through the database structure for retrieving data, allowing users to define and access data objects independently without altering the underlying database structure, utilizing metadata to organize and present data in response to user requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users directly modify relational database structures to extend functionality, then database adaptability improves, but device complexity and difficulty of operation increase significantly
Solution Approach 1:
The patent introduces a virtual database layer with virtual tables that act as an intermediary between users and the physical database structure. Users can define virtual tables with custom attributes and relationships without modifying the underlying physical tables. The system automatically generates SQL queries to traverse the physical database structure and retrieve data matching the virtual table definitions, enabling users to extend database functionality through high-level abstractions while shielding them from complex database management tasks.
2Adaptability or versatility
If users directly modify relational database structures to extend functionality, then database adaptability improves, but reliability decreases due to potential structural errors
Solution Approach 1:
The virtual database layer serves as a protective intermediary that prevents direct user access to and modification of the physical database structure. Users define virtual tables and attributes through a simplified interface, and the system automatically translates these definitions into proper SQL queries that maintain referential integrity and structural constraints. This abstraction layer isolates users from complex database management tasks, eliminating the risk of structural errors while preserving database reliability.
3Manufacturing precision
If extensive training is provided to users for database management, then manufacturing precision improves, but loss of time increases due to training requirements
Solution Approach 1:
The patent enables users to perform database extension tasks through an intuitive interface that automatically generates the necessary SQL statements and query logic. Users define virtual tables by specifying attributes and relationships through simple forms or configuration files, and the system self-service translates these definitions into optimized SQL queries that traverse the physical database structure. This eliminates the need for users to learn complex database management concepts while maintaining high precision in database implementation.
4Ease of operation
If virtual structures are used to extend database functionality, then ease of operation improves, but device complexity increases due to additional abstraction layers
Solution Approach 1:
The patent creates virtual copies of database tables and structures that mirror the physical database organization. Virtual tables are defined with attributes and relationships that correspond to underlying physical tables, allowing users to work with simplified representations of the data structure. The system automatically generates SQL queries that traverse the physical database structure based on virtual table definitions, providing users with an intuitive interface while maintaining a relatively simple overall system architecture.
Data Source
AI summary
A method, apparatus and computer program product are therefore provided for implementing requests for data using independent data objects. In this regard, the method, apparatus and computer program may receive a request for set of data. The request may include an identifier for the particular set of data. The method may further determine a structure of the set of data using an attribute table associated with one or more data objects, and generate a query using the determined structure of the set of data. The generated query may be executed to retrieve a set of data responsive to the request. The retrieved data may be used along with the determined structure to provide a response to the request.