Database Synchronization Adapter for Legacy Hierarchical Systems
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Solution Overview
Problem
Legacy database systems, particularly those based on hierarchical models, face challenges in data management and integration with modern relational databases due to their outdated technology and complex data structures, leading to difficulties in updating and maintaining data integrity and relationships.
Innovation Solution
A system and method for synchronizing data between relational and non-relational databases, using an agent to translate user requests into operations on both databases, enforce logical interconnections, and manage data consistency, allowing for transparent access and manipulation of data across both systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If legacy hierarchical database systems are used, then data can be stored in tree-like structures with linked records, but data management and integration with modern relational databases become complex and difficult to maintain
Solution Approach 1:
The patent employs an intermediary layer (translation service or adapter) that sits between the hierarchical database system and the relational database system. This intermediary translates data structures, queries, and operations between the two different database models, enabling integration without requiring direct complex mappings. The intermediary handles the complexity of translating tree-like hierarchical structures into relational table structures and vice versa, resolving the integration complexity issue while preserving data structure flexibility.
2Stability of the object's composition
If legacy hierarchical database systems are used, then existing data can be maintained, but updating and maintaining data integrity becomes difficult
Solution Approach 1:
The system implements self-service mechanisms where the translation layer automatically handles data synchronization, integrity validation, and conflict resolution between hierarchical and relational databases. Rather than requiring manual intervention to maintain data integrity across systems, the automated translation service continuously monitors and reconciles data states, performs validation rules, and maintains consistency without user involvement, thus improving ease of operation while preserving data stability.
3Reliability
If data is synchronized between relational and non-relational databases, then data consistency is improved, but system complexity increases
Solution Approach 1:
The synchronization system is segmented into distinct modular components: a translation service layer, a synchronization engine, validation modules, and conflict resolution handlers. Each component performs a specific function in the data synchronization process. This segmentation allows the system to manage complexity by breaking down the overall synchronization task into manageable, independently configurable modules, making the system easier to maintain and extend while achieving reliable data consistency across database types.
Data Source
AI summary
According to some aspects, a system is providing including a first database, at least one processor configured to communicate with the first database and an external database, and at least one processor-readable storage medium including processor-executable instructions that, when executed, cause the at least one processor to: receive a request from a user via a user interface, translate the request into at least one first operation on the first database and at least one second operation on the external database, and perform the at least one first operation and the at least one second operation.