Automated Database Orientation Transformation for ERP Modernization
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Solution Overview
Problem
Upgrading ERP systems from row-oriented to column-oriented databases is complex and time-consuming, requiring significant manual rewriting of applications, which poses challenges in modernization due to incompatibility issues between old and new versions.
Innovation Solution
The development of systems and methods for automated analysis and transformation of applications and databases from a row-oriented syntax to a column-oriented syntax, involving data extraction, reorientation of read and select operations, and code optimization for improved performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual rewriting of applications is performed to upgrade from row-oriented to column-oriented databases, then compatibility with new versions is improved, but time consumption and cost increase significantly
Solution Approach 1:
The system creates a copy of the source code and performs automated transformation on the copy, preserving the original while generating the upgraded version. This allows compatibility improvement without requiring time-consuming manual rewriting of the original codebase.
Solution Approach 2:
The system automatically changes the database orientation parameter from row-oriented to column-oriented through code transformation. This enables compatibility with new database versions by systematically modifying code constructs that interact with the database, reducing the time required for manual parameter updates.
2Adaptability or versatility
If manual rewriting of applications is performed to upgrade from row-oriented to column-oriented databases, then compatibility with new versions is improved, but cost increases significantly
Solution Approach 1:
The system performs self-service by automatically analyzing and transforming the codebase without requiring extensive manual intervention. The automated code transformation engine handles the upgrading process independently, significantly reducing the labor costs associated with manual rewriting while improving compatibility.
Solution Approach 2:
By working on a copied version of the codebase, the system eliminates the need for expensive manual rewriting of the original code. The automated transformation of the copy provides a cost-effective path to achieving compatibility with new database versions.
3Productivity
If automated transformation is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The automated transformation system is segmented into distinct functional modules: code analysis module, transformation rule engine, and code generation module. This segmentation improves productivity by enabling parallel processing while managing complexity through modular architecture, where each module handles a specific aspect of the transformation process.
Data Source
AI summary
The present application is directed towards systems and methods for automated analysis and transformation of databases and related applications and functions from a row-oriented syntax to a column-oriented syntax. An analyzer client executed by a processor of a client device may analyze a first database of a business management system comprising a plurality of arrays in a row-oriented syntax. A transformer executed by the processor may execute a first array of a second database having a column-oriented syntax. Iteratively, for each array of the plurality of arrays of the first database, the transformer may read an element at a first position of said array, and write the element to a next position of the first array of the second database.