Relational Database Structure with Segmented Metadata Tables
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Solution Overview
Problem
Existing relational databases face challenges in efficiently managing and maintaining data integrity and structure as they grow in size and complexity, requiring frequent modifications and optimizations, which hinder the development of new features and applications.
Innovation Solution
A relational database structure comprising four main tables - data fields, data tables, data records, and data columns - where the actual data elements are stored separately from their structure and relational information, allowing for flexible storage and management without altering the database structure, and enabling the addition of new data and features without modifying the existing structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in a traditional relational database structure, then data can be organized in tables with defined relations, but the database structure must be changed when new data fields or relations are added, requiring complex reformatting and maintenance
Solution Approach 1:
The patent segments the database into four distinct tables: data fields table (storing field definitions), data tables table (storing table structures), data records table (storing actual data), and data columns table (storing column information). This segmentation allows each component to be modified independently without affecting the overall database structure, enabling flexible addition of new fields and relations while maintaining structural stability.
Solution Approach 2:
The patent introduces intermediary tables (data tables table, data columns table, data records table) that act as mediators between the actual data and the database structure. These intermediary tables store metadata and relational information, allowing the database to adapt to new requirements by modifying the intermediary tables rather than the core data storage structure, thus reducing modification complexity.
2Adaptability or versatility
If the database structure is modified to accommodate new features, then new data can be stored, but data integrity must be maintained requiring database analysts to perform thorough tests and modifications
Solution Approach 1:
The patent implements preliminary action by storing complete structural definitions in the data fields table, data tables table, and data columns table before data is actually stored. This allows the database system to validate and verify the structure in advance, ensuring data integrity constraints are properly defined before data insertion, thereby maintaining reliability while allowing structural flexibility.
Solution Approach 2:
The patent establishes feedback mechanisms where the database management system automatically validates data against the structural definitions stored in the intermediary tables. When new fields or relations are added, the system can automatically check data integrity constraints and provide feedback on potential issues, reducing the need for manual testing while maintaining data reliability.
3Adaptability or versatility
If large amounts of data are stored in a flat text file, then flexibility and compatibility are maintained, but data retrieval and handling become very cumbersome and inefficient
Solution Approach 1:
The patent segments large amounts of data into organized tables with defined structures, where data is divided into logical units (tables, records, fields) that can be independently accessed and manipulated. This segmentation enables efficient data retrieval by allowing direct access to specific tables and records without reading through entire data sets, dramatically improving productivity while maintaining the flexibility to store diverse data types.
4Ease of manufacture
If the database structure remains constant over time, then maintenance and optimization needs are reduced, but the ability to accommodate new data requirements is limited
Solution Approach 1:
The patent implements dynamics by making the database structure configurable and adaptable through the intermediary tables. The data fields table, data tables table, and data columns table can be dynamically modified to accommodate new data requirements, while the core data storage mechanism remains stable. This allows the database to evolve over time without requiring fundamental structural changes, reducing maintenance effort while maintaining adaptability.
Data Source
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AI summary
The present invention is related to a relational database, stored in a computer memory of a computer device, and a database server comprising such a database, a database management system for managing and working with such a database and a method of storing, retrieving, altering and managing data in such a database. The present invention provides a relational database, stored in a computer memory, and comprising a plurality of data elements and a plurality of relational information of the plurality of data elements, wherein the relational database is comprised of a plurality of tables, at least comprising a data fields table, a data tables table a data records table and a data columns table, and wherein the plurality of data elements is comprised in the data fields table, the plurality of relational information of the plurality of data elements is comprised in the data tables table, the data records table and the data columns table; wherein the data tables table comprises a plurality of records defining at least one table of the relational database, the data records table comprises a plurality of records defining at least one record of the at least one table of the data tables table, the data columns table comprises a plurality of records defining at least one column of the at least one table of the data tables table.