Graph Data Structure for Microservice Relationship Persistence
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Solution Overview
Problem
Existing data-related processes, particularly microservices, face challenges in conducting aggregate analysis due to the lack of readily available relationships among data objects, which are often self-contained and independent, making it difficult to maintain autonomy while representing these relationships.
Innovation Solution
A centralized platform using graph data structures to capture and persist relationships between data objects across various microservices, allowing for the definition and visualization of custom data object types, attributes, and relationship types, enabling the creation of graph data representations that depict data object types and their relationships, and facilitating queries across multiple microservices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data objects are maintained within independent microservices to preserve autonomy, then service independence and flexibility are improved, but the ability to conduct aggregate analysis across services deteriorates
Solution Approach 1:
The patent introduces a graph data structure as an intermediary layer between independent microservices. This graph structure serves as a mediator that captures relationships among data objects across services without requiring the microservices themselves to be coupled. The graph acts as a central coordination mechanism that enables aggregate analysis while preserving the autonomy of individual microservices.
Solution Approach 2:
The patent transitions from traditional relational database structures to a graph data structure representation. This dimensional change allows relationships to be explicitly modeled as edges between nodes (data objects), enabling efficient traversal and aggregation across microservices without altering the microservices' internal independence.
2Device complexity
If conventional relational databases are used to store data across microservices, then data storage is simplified, but query performance and relationship representation deteriorate
Solution Approach 1:
The patent fundamentally changes the data structure parameter from tabular relational format to graph format. In this new parameter space, relationships are first-class citizens represented as explicit edges, enabling direct traversal and efficient querying without the joins and complex queries required in relational databases.
Data Source
AI summary
The present disclosure provides methods, apparatus, systems, computing devices, computing entities, and/or the like for providing persistent representations in graph data structures of relationships that exist among data objects found across different data-related processes to enable efficient querying of data from the different data-related processes.