Graph Database Object Templates for Efficient Data Population
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Solution Overview
Problem
Creating objects for graph databases with unstructured graphs is repetitive and time-consuming due to the lack of a structured data model, requiring individual access to nodes and links.
Innovation Solution
The method involves defining templates for graph databases, each corresponding to an object category, with anchor nodes and linked nodes for identifying and descriptive attributes, allowing for efficient object creation and data population by parsing received data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unstructured graphs are used in graph databases, then flexibility and adaptability are improved, but object creation becomes repetitive and time-consuming
Solution Approach 1:
The patent defines templates before object creation, establishing predefined structures with anchor nodes and linked nodes that specify required attributes and relationships. This preliminary structuring eliminates the need for repetitive individual node creation while maintaining flexibility, as the templates can be adapted to different object categories without redefining the entire graph structure each time.
Solution Approach 2:
The patent segments object creation into template instantiation and data population phases. Templates are predefined reusable structures that can be instantiated multiple times for different objects, while the actual data is populated separately. This segmentation separates the structural definition (done once) from the data filling (done repeatedly), significantly improving productivity.
2Adaptability or versatility
If individual node and link access is required, then data flexibility is maintained, but the object creation process becomes complex and time-consuming
Solution Approach 1:
The patent uses template copying where predefined template structures are replicated and instantiated for new objects. Instead of creating each node and link individually, the system copies the template pattern and fills in specific data, reducing the complexity of the creation process while maintaining data flexibility through the templated approach.
Solution Approach 2:
The templates are designed to be universal and multi-functional, capable of representing different object categories through a common structural framework. The same template mechanism can be applied across various object types, reducing the overall complexity by using a single reusable pattern rather than category-specific creation procedures.
3Productivity
If templates are defined with anchor nodes and linked nodes, then object creation efficiency is improved, but template definition complexity increases
Solution Approach 1:
The template definition is performed as a preliminary action during system setup or initialization, rather than during individual object creation. By defining the template structure once with anchor nodes and linked nodes, the system achieves high object creation efficiency for all subsequent instances without requiring complex definitions to be repeated for each object.
Data Source
AI summary
A method for generating a graph database includes defining plural templates of the graph database, each of the templates corresponding to a respective object category. Each of the templates includes nodes defining identifying attributes of an object in the object category. The method further includes selecting a first template to represent a first object corresponding to the object category of the first template and selecting a second template to represent a second object corresponding to the object category of the second template. The method further includes linking the first template to the second template by storing relationship data between a node of the first template and a node of the second template, and populating the first template and the second template by parsing received data of the first object and the second object.