Multi-System Data Archiving via Immutable Mutable Segmentation
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Solution Overview
Problem
Managing data archiving and recovery across multiple storage systems in complex environments with large data volumes is complicated, especially when dealing with immutable and mutable data types, and ensuring data integrity during these processes.
Innovation Solution
A system that stores and archives data across multiple storage systems, including database and flat file systems, by identifying and separating immutable and mutable data portions, and using an archive system to compress and decompress data while ensuring data integrity through hashing and verification methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is archived across multiple storage systems, then data redundancy and reliability are improved, but system complexity and management difficulty increase
Solution Approach 1:
The patent introduces an intermediary archiving system that acts as a mediator between multiple storage systems. This archiving system receives data from different storage systems, archives it centrally, and manages recovery operations, thereby reducing the complexity of direct multi-system coordination while maintaining data reliability across systems.
Solution Approach 2:
The archiving system performs multiple functions including data reception from various storage systems, data archiving, data verification, and recovery operations. This multi-functional approach consolidates what would otherwise require separate systems for each function, reducing overall system complexity while maintaining reliability.
2Quantity of substance
If data is compressed during archiving, then storage efficiency is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements periodic archiving operations where data is compressed and archived at scheduled intervals rather than continuously. This periodic approach allows computational resources to be allocated efficiently, reducing peak processing demands while maintaining effective storage utilization over time.
3Measurement precision
If data integrity verification is performed through hashing, then data accuracy is improved, but computational overhead increases
Solution Approach 1:
The patent creates hash copies of the original data as a simplified representation for verification purposes. Instead of performing complex verification on the full data set, the system computes hashes (compact copies) that can be efficiently stored and compared, maintaining data accuracy verification while significantly reducing computational overhead.
4Manufacturing precision
If immutable and mutable data are separated and stored differently, then data management precision is improved, but system complexity increases
Solution Approach 1:
The patent segments data into immutable and mutable categories, storing each type in appropriately designed storage systems. This segmentation allows each storage system to be optimized for its specific data type while maintaining clear boundaries and management protocols, improving data management precision without requiring a completely complex integrated system.
Data Source
AI summary
Mutable portions of data are stored in a first storage system and immutable portions of the data are stored in a second storage system. Immutable portions and mutable portions of the data associated with the same time period are initially archived. After a period of time since the initial archiving, the mutable portions of the data from the first storage system that have been modified are supplemental archived. Integrity verifications of successfully performing the initial archiving and supplemental archiving are stored.