Graph Query Translation Layer for Relational Databases
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Solution Overview
Problem
Existing graph databases are not suitable for integrated systems that require both graph and relational database queries, leading to inefficiencies such as data duplication and delayed updates, as they often force applications to replicate relational data and maintain separate copies, wasting storage and memory resources.
Innovation Solution
A computer-implemented method and system that translates graph database queries into relational database queries, allowing graph queries to operate on data stored in relational databases using a graph middle layer, which optimizes query execution and avoids maintaining duplicate data copies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If graph databases replicate relational data in specialized graph formats, then graph query capability is improved, but storage and memory resources are wasted
Solution Approach 1:
The patent introduces a translation layer that acts as an intermediary between graph query interfaces and relational database operations. This layer translates graph database queries into equivalent SQL queries, allowing the system to provide graph query functionality without actually storing data in specialized graph formats, thereby eliminating the need for duplicate data storage while maintaining graph analytics capability
Solution Approach 2:
Instead of creating physical copies of data in graph format, the patent creates virtual copies through query translation. The translation layer generates SQL queries that simulate graph database behavior by querying the existing relational data, providing the effect of having graph-format data without the actual duplication and storage overhead
2Speed
If graph databases maintain separate data copies, then graph query performance is improved, but data consistency deteriorates
Solution Approach 1:
The translation layer serves as a mediator that ensures data consistency by always querying the original relational database for the most current data. This eliminates the consistency problems associated with maintaining separate data copies, as the translation layer transparently accesses the authoritative data source while still providing graph query functionality
Solution Approach 2:
The patent replaces the mechanical approach of maintaining physical data copies with a virtual approach using query translation. Instead of mechanically replicating and synchronizing data between relational and graph formats, the system uses software-based translation that automatically ensures consistency by querying the single source of truth in the relational database
3Adaptability or versatility
If applications import data into specialized graph formats at runtime, then graph query capability is improved, but processing time and complexity increase
Solution Approach 1:
The patent performs the data format conversion action in advance by translating graph queries into SQL at query execution time rather than requiring pre-import of data into graph formats. This preliminary translation approach eliminates the time-consuming data import process while still enabling graph query capability, as the translation occurs only when queries are executed rather than requiring upfront data transformation
Data Source
AI summary
Techniques for augmenting relational databases with graph database capabilities are described. A graph database query requesting data from a graph database is received. The graph database includes a plurality of vertices and a plurality of edges. The graph database query is translated into a relational database query using one or more computer processors. The relational database query references a vertex table and an edge table in a relational database. Result data corresponding with the graph database query is retrieved from the relational database by executing the relational database query against the relational database.