Automated Database Release Management via Version Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Database automation faces challenges in maintaining the production version intact and ensuring seamless deployment of parallel release changes due to differences in development and deployment processes, particularly in managing incremental changes and primary key-foreign key relationships.
Innovation Solution
A system that uses a database modeling tool to generate scripts through reverse engineering, compares versions to identify changes, and automatically generates incremental scripts and packages, while defining execution sequences based on primary key-foreign key relationships to ensure error-free deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual database release management is used, then flexibility in handling different release versions is maintained, but the risk of errors increases and deployment efficiency decreases
Solution Approach 1:
The system enables self-service automated database release management by comparing database objects across versions, automatically identifying changes, and generating deployment scripts without manual intervention, thereby improving both reliability and efficiency
Solution Approach 2:
The patent replaces manual mechanical processes of database release management with an automated computer-based system that performs version comparison, change identification, and script generation, eliminating human error and increasing deployment speed
2Productivity
If parallel release changes are deployed without automated comparison, then deployment speed may increase, but the integrity of the production database cannot be ensured
Solution Approach 1:
The system performs preliminary automated comparison of database objects between versions before deployment, identifying all changes in advance and generating appropriate deployment scripts, ensuring integrity is maintained while enabling fast parallel releases
Solution Approach 2:
The system provides feedback by automatically comparing database versions and identifying changes, using this information to generate precise deployment scripts that maintain database integrity while enabling rapid deployment
3Measurement precision
If comprehensive comparison of all database objects is performed, then accurate identification of changes is achieved, but the time required for release preparation increases
Solution Approach 1:
The system segments the database into discrete objects (tables, views, procedures, functions) and compares them individually, enabling precise change detection while automating the process to minimize preparation time
Solution Approach 2:
The automated system performs comprehensive comparison of all database objects without manual intervention, achieving accurate change identification while reducing release preparation time through automation
4Adaptability or versatility
If the production database structure is modified directly during parallel development, then development flexibility is improved, but the risk of compromising production integrity increases
Solution Approach 1:
The system uses an intermediary automated comparison and script generation process between development changes and production deployment, allowing flexible parallel development while protecting production integrity through controlled, automated application of changes
5Reliability
If incremental scripts are generated automatically for each release, then deployment accuracy is improved, but the complexity of the release management system increases
Solution Approach 1:
The system achieves deployment accuracy through automated self-service generation of incremental scripts based on object comparison, managing complexity through automation rather than manual processes
Data Source
AI summary
Systems, computer program products, and methods are described herein for multi-release and parallel development of a database. The present invention is configured to determine a first version of a database release, wherein the first version is based on a first script; receive an incremental script associated with the first version of the database release; implement a database modeling tool to generate a second script, thereby creating a second version of the database release based on at least the first script and the incremental script; automatically generate an incremental database package based on at least the second version of the database release; and deploy the incremental database package, wherein deploying further comprises creating a second version of the database release based on the second script, wherein the second script is a baseline script for the second version of the database release.