Streaming Data Conversion and Replication for Cross-Format Migration
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Solution Overview
Problem
Current data replication technologies face challenges in maintaining real-time data availability and integrity during outages, particularly when migrating data between systems with different formats, such as Big Endian and Little Endian, or between 32-bit and 64-bit systems, and across different character sets, which can lead to data loss and performance degradation.
Innovation Solution
A system and method for streaming data conversion and replication that includes a primary data store, a secondary data store, a network connection, a replicator, and a conversion unit. The replicator ensures data replication, while the conversion unit, comprising a processor and memory with a conversion algorithm, intercepts and converts data streams in real-time, enabling byte order, byte size, and character set conversions without interrupting data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous replication is used to ensure real-time data consistency, then data integrity is improved, but application performance deteriorates due to network round trip delays
Solution Approach 1:
The system segments the replication process into independent components: the primary data store handles application writes locally without waiting for secondary confirmation, while the replicator independently manages data transmission to secondary stores. This segmentation allows application performance to remain high while replication integrity is maintained through the replicator's error handling and retry mechanisms.
2Productivity
If asynchronous replication is used to maintain application performance, then productivity is improved, but data reliability deteriorates due to potential loss of queued transactions during outages
Solution Approach 1:
The replicator implements beforehand cushioning by maintaining a queue of replicated writes and implementing retry logic. When the secondary data store becomes available again after an outage, the replicator resumes sending queued writes, ensuring data integrity is restored without affecting application performance during the outage period.
3Adaptability or versatility
If data conversion is performed during replication between different formats, then adaptability is improved, but system complexity increases due to additional conversion components
Solution Approach 1:
The replicator is designed with multi-functionality, serving both as a data transmission component and a format conversion component. The same replicator that manages asynchronous replication also performs endianess conversion, byte size conversion, and character set conversion, eliminating the need for separate conversion components and reducing overall system complexity.
4Adaptability or versatility
If real-time conversion is performed on data streams, then adaptability is improved, but processing time increases due to conversion operations
Solution Approach 1:
The conversion operations are performed continuously on the data stream as it passes through the replicator, rather than as discrete batch operations. This continuous conversion approach minimizes processing delays by integrating conversion into the normal replication flow, ensuring format compatibility without significant time loss.
Data Source
AI summary
A system and method are provided for integrating conversion and replication of a data stream for replicating data stored in a primary data store. The method includes streaming a replicated data stream from the primary data store to a secondary data store. The method includes intercepting the replicated data stream in route to the secondary data store. The method also provides for converting the replicated data stream.