Database Change Management via Model Delta Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current database change management systems are vendor-specific, error-prone, and lack efficiency due to manual data definition language (DDL) construction, limited SQL capabilities, and context dependency, leading to cascading errors and reduced reusability across different database vendors.
Innovation Solution
A computer-implemented method using a delta definition structure to compare a base model with a desired model, identifying structural database entity changes and applying them to form a resulting model, while reducing dependency on specific database states and vendors through a structured approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual data definition language (DDL) construction is used to change database structure, then vendor-specific database changes can be implemented, but the process becomes error-prone and complex
Solution Approach 1:
The patent introduces a change management system as an intermediary layer between the desired database change and the actual DDL execution. This system automatically generates vendor-specific DDL statements by comparing base and target models, eliminating manual construction errors while maintaining vendor-specific adaptability through automated translation to the appropriate DDL syntax.
Solution Approach 2:
The patent replaces manual mechanical construction of DDL statements with an automated computational system. The system automatically compares database models, identifies differences, and generates appropriate DDL statements, substituting the error-prone manual process with automated model comparison and code generation mechanisms.
2Productivity
If SQL data definition language is used to propagate database changes, then database structure can be modified, but the statements are limited and require extensive preprocessing and postprocessing steps
Solution Approach 1:
The patent performs preliminary model comparison between base and target database models to automatically identify all required changes before execution. This preliminary analysis includes comparing structural elements, dependencies, and implications, preparing a comprehensive change plan that eliminates the need for extensive manual preprocessing and postprocessing steps during actual DDL execution.
Solution Approach 2:
The patent implements continuous automated monitoring and execution of database changes through a unified system that handles the entire change lifecycle. The system continuously compares models, identifies changes, generates DDL statements, executes them, and monitors results, providing continuous useful action that eliminates discrete preprocessing and postprocessing steps.
3Ease of operation
If proprietary extensions like Change Definition Language are used to represent structural changes, then change representation is simplified, but the solution becomes context-dependent and not easily integrated throughout an entire enterprise
Solution Approach 1:
The patent creates a universal change management system that can operate across multiple database vendors and contexts. The system uses a standardized internal representation of database models and changes that can be translated to various vendor-specific DDL statements, making it universally applicable throughout an enterprise without requiring vendor-specific customizations.
Solution Approach 2:
The patent changes the representation parameters from vendor-specific proprietary languages to a standardized, vendor-agnostic change representation. The system uses abstract data models and standardized change descriptions that can be dynamically translated to appropriate vendor-specific syntax, enabling enterprise-wide integration while maintaining operational simplicity.
4Reliability
If error validation steps are performed before processing changes, then invalid database structures are prevented, but the process time is increased and changes cannot be made without resolution
Solution Approach 1:
The patent performs comprehensive error validation as a preliminary automated step during model comparison. The system automatically detects potential errors in change plans, validates database structure validity, and resolves conflicts before DDL execution, eliminating the need for time-consuming manual validation and resolution steps during the change process.
Solution Approach 2:
The patent implements automated feedback mechanisms that continuously monitor database structure validity during the change process. The system provides real-time feedback on potential errors and validation results, automatically adjusting change plans to ensure validity without requiring manual intervention or time-consuming validation steps.
5Manufacturing precision
If detailed knowledge of database capabilities and limitations is required to use data definition language, then precise database changes can be made, but the system becomes complex and difficult to use
Solution Approach 1:
The patent introduces an intelligent intermediary system that automatically adapts change statements to specific database capabilities and limitations. The system analyzes the target database's capabilities, selects appropriate DDL statements, and adjusts change parameters automatically, providing precise database changes without requiring users to understand or manually configure complex database-specific parameters.
Data Source
AI summary
A computer implemented method, apparatus, and computer usable program code to compare a base model to a desired model to identify changes needed to form the desired model. The changes are placed in a data structure containing a set of elements, wherein the set of elements identify a set of structural database entities and a set of changes to the set of structural database entities. Changes are made to a target model using the data structure to form a resulting model.