Relational Database Schema Adaptation via Automated Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual intervention to synchronize schema changes between source and destination databases in relational database management systems is inefficient and prone to errors.
Innovation Solution
A method where a relational database management system (RDMS) receives data, determines its schema, compares it to existing schemas, applies schema changes if necessary, and writes the data to the database, thereby synchronizing the destination schema with the source schema.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to synchronize schema changes between source and destination databases, then data integrity can be maintained through careful review, but the process is inefficient and time-consuming
Solution Approach 1:
The system performs self-service by automatically detecting schema changes in the source database and applying them to the destination database without requiring manual intervention. The schema synchronization process is autonomous, with the system independently comparing schemas, identifying differences, and executing change applications while maintaining data integrity through built-in validation mechanisms.
Solution Approach 2:
The system performs preliminary actions by first comparing the source and destination schemas to identify differences before applying any changes. This preliminary comparison step allows the system to plan the synchronization process, validate compatibility, and prepare the necessary change scripts before actually modifying the destination database schema.
2Reliability
If manual schema synchronization is performed, then changes can be carefully reviewed, but systems experience extended unavailability during schema syncing
Solution Approach 1:
The system implements periodic action by performing schema comparisons and synchronization in scheduled intervals rather than continuously blocking operations. The automatic schema synchronization runs at predetermined times or triggered by specific events, allowing the system to maintain normal operations between synchronization cycles while still keeping schemas up-to-date.
Solution Approach 2:
The system uses an intermediary approach by introducing a schema comparison and validation layer between the source and destination databases. This intermediary process analyzes schema differences and generates change scripts without directly blocking data operations, allowing schema synchronization to proceed with minimal impact on system availability.
3Productivity
If automated schema adaptation is implemented, then schema syncing time is reduced, but the system complexity increases
Solution Approach 1:
The system achieves universality by designing a multi-functional schema synchronization module that can handle various types of schema changes (table creation, column modifications, data type changes) through a unified automated process. This single module performs multiple functions including schema comparison, change detection, script generation, and validation, reducing the need for separate complex systems for each synchronization task.
Solution Approach 2:
The system replaces manual mechanical operations with automated computational processes. Instead of requiring manual comparison and application of schema changes, the system uses automated algorithms to detect differences, generate change scripts, and apply modifications. This substitution of manual processes with automated systems increases syncing speed while the modular design keeps complexity manageable.
Data Source
AI summary
An example methodology includes, by a relational database management system (RDMS), receiving data for writing to a relational database, determining a schema associated with the data, and comparing the schema to existing schemas in the relational database to determine whether there is a schema change. The method also includes, responsive to a determination that there is a schema change, applying the schema change to the relational database, so as to adapt a schema of the relational database to the schema associated with the data, wherein the determination that there is a schema change is based on the comparing the schema to the existing schemas. The method further includes writing, by the RDMS, the data to the relational database.


