Conditional Database Synchronization Using Log-Based Update Flags
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cross-database synchronization methods, particularly in enterprise environments, are inefficient and time-consuming due to sequential querying and updating of large datasets, which do not scale well.
Innovation Solution
A method involving a processor that retrieves timestamps from a first database, queries a second database for update and error indicators, and conditionally updates a third database based on these indicators, using a pending flag to determine eligibility for updates, allowing parallel processing and reducing redundant queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic sequential batch updates are performed to synchronize data across databases, then data synchronization is achieved, but the process becomes excessively time-consuming and does not scale efficiently for large datasets
Solution Approach 1:
The patent segments the synchronization process by introducing a log database that tracks individual record update status across multiple databases. Instead of processing entire batches sequentially, the system divides the synchronization task into discrete, trackable units (individual records) and processes them independently based on their specific update status, enabling parallel processing and reducing overall synchronization time.
Solution Approach 2:
The patent implements feedback mechanisms through update indicators and error indicators stored in the log database. These indicators provide real-time feedback about the synchronization status of individual records, allowing the system to dynamically adjust processing priorities, skip already-updated records, and focus only on records that need synchronization, thereby significantly reducing time loss.
2Reliability
If sequential querying and updating of large batches of records is performed, then data synchronization is completed, but computational complexity and processing time increase excessively
Solution Approach 1:
The patent extracts the synchronization tracking function from the main processing logic by introducing a dedicated log database. This log database stores individual record status information (update indicators and error indicators), separating the complexity of tracking from the complexity of processing. This extraction allows the main synchronization process to focus on data transfer while the log database handles the complex tracking and coordination tasks.
3Reliability
If redundant queries and updates are performed to ensure data consistency, then data synchronization reliability is improved, but network bandwidth consumption and processing time increase
Solution Approach 1:
The patent performs preliminary actions by querying the log database before processing each record to determine its update status. The update indicator and error indicator are retrieved in advance, allowing the system to pre-determine whether a record needs full processing or can be skipped. This preliminary checking prevents redundant queries and updates to already-synchronized records, reducing network bandwidth consumption while maintaining data consistency.
Data Source
AI summary
This disclosure describes techniques for conditionally updating a target database using reference data received from a reference database. In some cases, an update management system is configured to periodically retrieve reference timestamps from the reference database and determine whether corresponding fields in the target database should be updated based on those reference timestamps. The determination of whether to update the target database may be based on automated checks of error indicators and update indicators maintained in a log database that is local to the update management system. An error indicator may represent whether a data record is associated with any error conditions that would prevent updating the target database based on that data record. An update indicator may represent whether the reference timestamp associated with a data record has already been used to successfully update the target database.