Replication Server Trigger-Based Change Logging
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Solution Overview
Problem
Current data replication methods face challenges in maintaining consistency and efficiently synchronizing changes between source and target systems, particularly in business applications and database systems, where changes need to be tracked and replicated accurately across different data types and storage formats.
Innovation Solution
The method involves using database triggers at the source system to record changes in a log, extracting and confirming these changes for consistency, and then providing them to a replication server to write the changes to the target system, which can be an in-memory or column-oriented database, ensuring synchronization and data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If database triggers are used to track changes at the source system, then data consistency between source and target systems is improved, but system complexity increases due to trigger maintenance and log management
Solution Approach 1:
A replication server is introduced as an intermediary component between the source system and target system. The server captures change events from triggers at the source system, processes them through a standardized interface, and applies them to the target system. This intermediary absorbs the complexity of trigger management and log processing, isolating it from both source and target systems while ensuring data consistency.
Solution Approach 2:
The change tracking functionality is extracted from the target system and centralized at the source system through triggers. Instead of implementing complex change detection mechanisms at the target system, the patent extracts the tracking function to the source system where triggers automatically capture changes, simplifying the overall architecture while maintaining reliability.
2Reliability
If comprehensive change logging is implemented to ensure consistency, then data integrity is improved, but processing time and storage requirements increase
Solution Approach 1:
Change logging is performed preliminarily at the source system through triggers that capture changes immediately when they occur. By recording changes at the source before replication, the system ensures data integrity without delaying target system updates. The log serves as a pre-prepared record that can be efficiently processed and applied to the target system.
Solution Approach 2:
Instead of transferring entire datasets or complex transaction logs, the patent copies only the essential change information (inserts, updates, deletes) captured by triggers. This selective copying of change events reduces the volume of data that needs to be processed and transmitted, minimizing processing time while maintaining complete data integrity through the replication server.
Data Source
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AI summary
Methods and apparatus, including computer program products, are provided for data replication. In one aspect, there is provided a computer-implemented method. The method may include providing an initial load of a data item from a source system to a target system, wherein the data item is associated with a trigger maintained at the source system; recording a change in a log, when a change to the data item at the source system causes the trigger to prompt the recording; extracting the change from the log to enable at least a confirmation of a consistency of the change; and providing the extracted change to a replication server configured to write the change to the target system. Related apparatus, systems, methods, and articles are also described.