Data Replication via Staging Tables for Large Data Centers
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Solution Overview
Problem
Current data replication methods, such as SQL replication and mirroring, are inadequate for replicating large amounts of data across two data centers, necessitating a more efficient process.
Innovation Solution
A computer-implemented method and apparatus that transfers data from a database to a staging table, extracts and transforms it, and then transmits the data to another computing system's database, utilizing a master package to manage the process and minimize impact on operational systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SQL replication or mirroring is used to replicate data, then data consistency is maintained, but the process becomes imprudent when replicating large amounts of data across data centers
Solution Approach 1:
The patent segments the data replication process into distinct phases: initial full data transfer, subsequent incremental changes tracking, and staged loading. This segmentation allows large datasets to be replicated systematically rather than as a single overwhelming operation, making the process practical for data center replication.
Solution Approach 2:
The patent introduces intermediary tables (staging tables, change tracking tables) that serve as buffer zones between source and destination databases. These intermediaries decouple the replication process from direct database-to-database replication, enabling more flexible and manageable data transfer across data centers.
2Adaptability or versatility
If data is replicated across data centers, then data availability is improved, but the complexity of the replication process increases
Solution Approach 1:
The patent creates a universal replication framework that handles both initial full data loads and subsequent incremental changes through a unified process. The same infrastructure and procedures manage different types of data replication scenarios, reducing overall system complexity despite the multi-data center environment.
Solution Approach 2:
The patent performs preliminary actions by pre-configuring change tracking tables and staging areas before data replication begins. This preparation work simplifies the actual replication process by having all necessary structures ready in advance, reducing complexity during execution.
3Ease of operation
If traditional replication methods are used, then implementation is straightforward, but they cannot handle large amounts of data efficiently
Solution Approach 1:
The patent changes key parameters of the replication process by using change tracking tables to monitor only modified records rather than replicating entire datasets. This parameter change from full-data replication to incremental-change replication dramatically improves efficiency while maintaining operational simplicity through automated tracking.
4Manufacturing precision
If data transformation is performed during replication, then data quality is improved, but the processing time increases
Solution Approach 1:
The patent maintains continuity of useful action by performing data transformations in the background during data loading operations. Rather than completing all transformations before loading, the system continuously transforms and loads data in parallel, reducing total processing time while maintaining data quality through consistent transformation application.
Data Source
AI summary
An apparatus, computer-implemented method, and computer program are provided. In one embodiment, data is transferred from a database to a staging table in another database. The data is extracted from the staging table in order to transform the data, and the extracted data is transmitted to a database of another computing system.