Multi-partitioned Global Data System Routing
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Solution Overview
Problem
Current data management systems face challenges in managing data records across multiple geographical regions due to varying regulatory requirements, which restrict data movement across borders while also needing to ensure fast and broad access to records globally, leading to conflicting demands for performance and compliance with privacy laws.
Innovation Solution
A distributed data management system that routes requests based on placement condition rules, verifies these rules for data records, and uses global unique identifiers to ensure compliance with regulatory requirements by storing data in permitted locations, allowing for replication and access while maintaining referential integrity and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in multiple geographical regions to enable fast and broad access globally, then data access performance is improved, but compliance with data privacy regulations deteriorates due to varying regulatory requirements that restrict data movement across borders
Solution Approach 1:
The system segments data storage by geographical regions, creating separate data partitions in different locations. Each partition is governed by local placement condition rules that reflect regional data privacy regulations. This segmentation allows the system to store data closer to users for fast access while ensuring each region's data remains subject to its own regulatory constraints.
Solution Approach 2:
The system applies local quality by implementing region-specific data placement policies where each geographical region has customized access and storage rules. The endpoint management component retrieves placement condition rules from the configuration component based on the specific data record and target region, ensuring local regulatory requirements are met while maintaining global data accessibility.
2Reliability
If data is restricted to specific geographical locations to comply with privacy laws, then compliance with data privacy regulations is improved, but data access performance deteriorates due to limited access locations
Solution Approach 1:
The system adds a regulatory compliance dimension to the traditional data access model. Instead of only considering geographical proximity for data access, the system incorporates placement condition rules that evaluate both location and regulatory constraints. This multi-dimensional approach allows data to be accessed from multiple locations when permitted by regulations, optimizing performance without sacrificing compliance.
Solution Approach 2:
The endpoint management component acts as an intermediary between data access requests and stored data records. It retrieves placement condition rules from the configuration component and evaluates whether the requested access complies with regional regulations before allowing data retrieval. This intermediary layer enables compliant data sharing across regions by mediating access based on regulatory requirements.
3Productivity
If a distributed data management system is implemented to enable global data access, then system scalability is improved, but system complexity increases due to managing placement condition rules across multiple nodes
Solution Approach 1:
The configuration component serves multiple functions: it stores placement condition rules, retrieves them for endpoint management, and provides a centralized repository for all regulatory policies across the distributed system. This universal component reduces complexity by consolidating rule management in a single location that serves the entire distributed network, rather than requiring each node to independently manage its own rules.
Solution Approach 2:
The endpoint management component autonomously retrieves and applies placement condition rules from the configuration component without requiring manual intervention or complex coordination between nodes. Each endpoint independently evaluates its own data access requests against the retrieved rules, enabling the distributed system to self-manage compliance without increasing operational complexity.
Data Source
AI summary
A computer-implemented method for managing data records subject to placement condition rules in a distributed data management system comprising a plurality of nodes. The method may include receiving, by an endpoint management component of the distributed data management system, a request for a data record. The method may also include routing, by the endpoint management component of the distributed data management system, the request to a node of the distributed data management system. The method may also include upon determining that the request is a create request, verifying, by a service component of the distributed data management system, a placement condition rule for the data record, where the placement condition rule is retrieved from a configuration component of the distributed data management system.