Cross-Database Querying via Identifier Segmentation
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Solution Overview
Problem
Existing techniques for querying multiple independent databases with complex queries are inadequate, as they often require merging large datasets, compromise security, and violate privacy restrictions, especially when databases are owned by different entities or located in different systems.
Innovation Solution
A method that splits a single query into filtering and target queries, allowing only identifiers of matching entries to be transmitted between databases, ensuring secure and private data access without merging datasets, using a central controller or local database agents to manage queries across independent databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is merged from multiple independent databases into a single dataset to satisfy complex queries, then query capability is improved, but data security and privacy are compromised
Solution Approach 1:
The system segments the query processing into multiple independent stages, where each database remains physically separate and processes only its own data. Filtering queries are executed independently on each database to produce identifier sets, which are then combined without exposing actual data records. This segmentation maintains data security while enabling complex cross-database queries.
Solution Approach 2:
The system introduces an intermediary layer that coordinates between multiple independent databases. This intermediary receives filtering queries, distributes them to appropriate databases, collects identifier results, and synthesizes final answers without any database exposing its actual data records. The intermediary acts as a mediator that enables cross-database querying while preserving data privacy through controlled information exchange.
2Adaptability or versatility
If full read access is granted to databases to enable cross-database queries, then query flexibility is improved, but access control and security management deteriorate
Solution Approach 1:
The system implements partial action by granting databases only the specific access they need to fulfill query requirements. Each database receives filtering queries that target specific data subsets and returns only identifier information, not full data access. This partial access approach maintains query flexibility while improving security management by limiting exposure to minimum necessary information.
3Loss of information
If data is transferred between databases to satisfy queries, then query completeness is improved, but data transfer complexity and security risks increase
Solution Approach 1:
The system extracts only the essential identifier information from database results, separating this minimal necessary data from the full data records. By extracting and transmitting only identifiers rather than complete data sets, the system achieves query completeness across multiple databases while dramatically reducing transfer complexity and security risks associated with moving large volumes of sensitive information.
Data Source
AI summary
A method of accessing multiple independent databases with a single query having multiple expressions involves deriving from a single query at least one filtering query, searching a first one of the multiple independent databases using the at least one filtering query, applying identifiers only of the filtering set of target entries and the target query to a second one of the multiple independent databases and generating a set of result entries from the second database which thereby satisfy the filtering expression and the target expression.