Data Replication System with Intermediary Mediator
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current computing systems face challenges in efficiently integrating and replicating data across different technologies and systems, lacking a comprehensive solution for managing data replication, field mapping, hierarchical organization, and replication filtering.
Innovation Solution
A system that provides a graphical user interface for configuring data replication between computing systems, employing techniques for field mapping, hierarchical data organization, and replication filtering, using access tokens for secure connections, and supporting various communication protocols for data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data replication is performed across multiple computing systems with different technologies, then data integration capability is improved, but system complexity increases
Solution Approach 1:
The patent employs an intermediary system that acts as a mediator between multiple computing systems with different technologies. This intermediary handles the complex tasks of field mapping, data transformation, and protocol adaptation, allowing source systems and target systems to communicate without direct complex interactions. The intermediary abstracts the heterogeneity of different systems, providing a unified interface for data replication while managing the underlying complexity internally.
Solution Approach 2:
The patent implements a universal data replication framework that can handle multiple data types, protocols, and system architectures through a single unified system. The field mapping mechanism and configuration interface provide multi-functional capabilities to adapt to various source and target systems, enabling one system to serve multiple purposes across different technological platforms without requiring separate specialized systems for each integration scenario.
2Manufacturing precision
If comprehensive data replication configuration is implemented, then data management precision is improved, but configuration complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically performs field mapping, data transformation, and replication configuration based on predefined schemas and metadata. The system can autonomously identify corresponding fields between different data models, apply appropriate transformations, and manage replication parameters without requiring manual configuration for each data element, thereby achieving precise data management with reduced configuration overhead.
Solution Approach 2:
The patent employs preliminary action by pre-defining field mappings, data transformation rules, and replication configurations before actual data replication occurs. The system prepares templates, schemas, and mapping relationships in advance, allowing the replication process to execute with high precision using pre-configured parameters rather than requiring complex real-time configuration decisions during data replication.
3Reliability
If secure access tokens are used for system connections, then connection security is improved, but authentication overhead increases
Solution Approach 1:
The patent implements preliminary authentication where access tokens are obtained and cached before actual data replication operations. The system performs authentication in advance, stores the access tokens securely, and reuses them for subsequent replication tasks, avoiding repeated authentication cycles. This preliminary action ensures secure connections while minimizing the time overhead associated with authentication during the actual data replication process.
4Loss of information
If hierarchical data organization is implemented, then data structure clarity is improved, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing data into hierarchical levels and organizing it into structured segments with clear parent-child relationships. The field mapping mechanism segments data fields into logical groups based on their hierarchical position, allowing the system to process and manage large volumes of data by breaking them down into manageable hierarchical units. This segmentation provides structural clarity while enabling efficient processing through divide-and-conquer strategies.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium storing a program that receives, at a first system, a first configuration for replicating a first type of data managed by the first system to a second system. The program further receives, at a third system, a second configuration for replicating a second type of data managed by the third system to the second system. The program also replicates a first set of data having the first type of data from the first system to the second system based on the first configuration. The program further replicates a second set of data having the second type of data from the third system to the second system based on the second configuration. The program also receives a third set of data from the second system, the third set of data generated by the second system based on the first and second sets of data.