Graph Data Modeling Tool for Multi-Model Query Isolation
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Solution Overview
Problem
Existing graph databases struggle with efficient data modeling and query building, particularly in property graph databases, as they lack user-friendly tools for creating and maintaining data models, managing interconnections, and ensuring data security and privacy across multiple data models.
Innovation Solution
A visual tool is provided for data modeling and query statement building, enabling collaborative data model development, secure multi-tenant architecture, and efficient storage of multiple data models as subgraphs within a single graph database, using a property graph structure with UUIDs for unique identification and auto-save features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data models are stored in a graph database without a structured approach, then data storage capacity increases, but data organization and retrieval efficiency deteriorate
Solution Approach 1:
The patent segments the graph database into multiple subgraphs, where each subgraph represents a distinct data model. This segmentation allows multiple data models to coexist without interference while maintaining efficient retrieval through subgraph-specific queries. The database is divided into isolated computational contexts, each optimized for its specific data model.
Solution Approach 2:
The patent introduces a subgraph root node as an intermediary entity that manages the relationship between the global query interface and individual data models. This root node acts as a mediator that routes queries to the appropriate subgraph and manages cross-subgraph relationships, enabling efficient retrieval without requiring full database scans.
2Ease of operation
If a visual tool is provided for data modeling, then ease of operation improves, but device complexity increases
Solution Approach 1:
The visual data modeling tool enables users to create and manage graph data models through intuitive graphical interfaces without requiring deep knowledge of graph database internals. The system provides self-service capabilities where users can define schemas, relationships, and queries through visual elements rather than complex code, abstracting away the underlying complexity.
Solution Approach 2:
The visual tool acts as an intermediary layer between the user and the graph database engine. It translates user-friendly visual operations into appropriate database commands and data structures, shielding users from the complexity of direct database interaction while maintaining full functionality.
3Productivity
If collaborative data model development is enabled, then productivity improves, but data security and privacy management becomes more complex
Solution Approach 1:
The patent segments data access permissions at the subgraph level, allowing different users and groups to have granular access control over specific data models. This segmentation enables collaborative development where team members can work on different subgraphs simultaneously with appropriate permissions, maintaining security without hindering collaboration.
Solution Approach 2:
The system implements multi-tenant architecture where each tenant has an isolated copy of the data model structure and data within their designated subgraphs. This copying approach allows multiple organizations to collaborate on the same platform while maintaining data privacy through logical isolation, enabling productivity without compromising security.
Data Source
AI summary
A system is disclosed to build and store a conceptual model and queries for a graph database. In various embodiments, data defining one or more aspects of a conceptual model associated with a graph database is received. A logical model of the conceptual model is created based at least in part on the conceptual model. The logical model includes information defining how data is physically stored. A set of data that represents the conceptual model is stored as a graph that includes one or more nodes to represent each of the following: conceptual model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.