Hybrid Graph Relational Database Architecture for Efficient Merging
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Solution Overview
Problem
Existing graph storage architectures face inefficiencies in managing and merging large sets of graphs, particularly in handling redundant data and identifying common elements or patterns across multiple graphs.
Innovation Solution
A multi-graph search and merge engine that combines graph and relational databases, allowing for the search and merging of graphs based on node or subgraph profiles, and displaying the merged results, while retaining the distinct identities of the original graphs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If graphs are stored in a single database architecture, then storage simplicity is maintained, but inefficiencies arise in managing and merging large sets of graphs with redundant data
Solution Approach 1:
The patent segments the database architecture into two distinct components: a graph database for storing graph data and a relational database for storing metadata. This segmentation allows each database type to optimize for its specific data structure, improving efficiency in managing and merging graphs while reducing redundant data storage.
Solution Approach 2:
The patent introduces a new dimension to the storage architecture by adding metadata storage alongside graph data storage. This dual-layer approach enables efficient graph operations while maintaining data integrity and reducing redundancy through centralized metadata management.
2Reliability
If redundant graph storage is maintained, then data integrity across multiple graphs is preserved, but storage efficiency and merging capability deteriorate
Solution Approach 1:
The patent extracts common metadata from multiple graph instances and stores it centrally in the relational database. This extraction eliminates redundant storage while preserving data integrity, as the metadata serves as a single source of truth that can be referenced by multiple graphs.
Solution Approach 2:
The metadata stored in the relational database serves multiple functions: it provides data integrity constraints, enables efficient graph merging through common element identification, and supports search operations across the graph set. This universal metadata structure replaces multiple redundant copies.
3Productivity
If a hybrid database architecture is implemented, then efficiency in searching and merging graphs improves, but system complexity increases
Solution Approach 1:
The patent combines graph database and relational database technologies into a unified hybrid architecture. This merging leverages the strengths of both systems: the graph database excels at storing and querying graph structures, while the relational database provides efficient metadata management and data integrity enforcement, together enabling superior search and merge operations.
Solution Approach 2:
The patent introduces a coordination layer that acts as an intermediary between the graph database and relational database. This mediator manages the interaction between the two systems, handling queries that span both data types and coordinating graph merging operations, thereby simplifying the complexity of the hybrid architecture.
Data Source
AI summary
Aspects of the disclosure relate to searching a dual database graph. The dual database graph is resident on a dual database graph platform. The platform includes two or more nodes interconnected by one or more edges. The graph database stores graph data corresponding to the graph(s) and a relational database for storing metadata corresponding to the graph(s). The method includes receiving as input a search criterion. The search criterion may include a plurality of data points corresponding to a relational database node profile or a relational database subgraph profile. The platform may search the relational database for a subset of graphs that each includes a relational database node or a relational database subgraph that matches the node profile or subgraph profile of the search criterion. The platform may then retrieve a relational database node or a relational database subgraph that matches the node profile or subgraph profile.