Hybrid Query Engine Integrating Relational and Graph Databases
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Solution Overview
Problem
Current systems face challenges in efficiently processing queries that combine relational and graph database operations, as they often require complex coding and lack seamless integration between different database types, leading to inefficiencies in data retrieval and storage.
Innovation Solution
A hybrid query engine that processes queries formatted in relational database languages (like SQL) with embedded graph database queries, utilizing an Open Cypher Function framework to communicate with graph database engines and join results, allowing for seamless execution of both relational and graph database operations without altering the SQL query engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex coding is used to integrate relational and graph database operations, then functionality is achieved, but system complexity and ease of operation deteriorate
Solution Approach 1:
The patent introduces an intermediary translation layer that automatically converts relational database queries into graph database queries. This mediator handles the complexity of integration internally, allowing users to write simple SQL queries without needing to understand graph database syntax or complex integration logic. The translation layer acts as the intermediary that resolves the contradiction by hiding complexity while maintaining versatility.
Solution Approach 2:
The system implements a universal query interface that can handle both relational and graph database operations through a single SQL-like language. This multi-functional approach allows the same query syntax to work across different database types, eliminating the need for complex coding to integrate different database operations. The universal interface resolves the contradiction by providing adaptability without increasing operational complexity.
2Productivity
If separate processing is used for relational and graph database queries, then processing simplicity is maintained, but productivity and data retrieval efficiency deteriorate
Solution Approach 1:
The patent merges the processing of relational and graph database queries into a unified system architecture. The query translation and execution framework combines both database operations into a single streamlined process, allowing simultaneous optimization of both query types. This merging improves productivity by enabling efficient hybrid query processing while managing system integration through a cohesive architecture rather than separate disparate systems.
Solution Approach 2:
The system performs preliminary translation of relational queries into graph database queries before execution. This advance preparation allows the graph database engine to optimize query execution in advance, improving data retrieval speed. The preliminary action of query translation and planning resolves the contradiction by preparing queries efficiently before execution, enhancing productivity while keeping the integration process manageable through automated preprocessing.
3Ease of operation
If seamless integration is implemented between database types, then ease of operation improves, but device complexity increases
Solution Approach 1:
The patent extracts the integration complexity from the user's operational view and places it in the system's internal architecture. Users interact with a simplified SQL interface without seeing or managing the complex integration mechanisms. The translation framework, query mapping, and execution coordination are extracted and hidden within the system, providing ease of operation while containing device complexity within the system boundaries rather than exposing it to users.
Data Source
AI summary
A technique includes in a relational database query engine, receiving a query associated with a relational data structure. The received query includes a database graph query. The technique includes using the relational database query engine to integrate a result acquired from the graph database engine into a result provided by the relational database query engine to the received query.