Recursive Query Transliteration for Database Compatibility

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Solution Overview

Problem

Existing technologies face challenges in efficiently and accurately translating machine interpretable language queries across different databases, due to incompatibilities and the need for real-time processing, which often results in errors and increased costs.

Innovation Solution

A computing platform with a custom driver and query translation library that translates database queries from one format to another by using pre-verified query keys and a transliteration process, ensuring accurate and efficient execution across different databases.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual translation between different machine interpretable languages is performed, then compatibility between databases is improved, but time consumption and cost increase significantly

Engineering Contradiction:

Improvedatabase compatibilityVSAvoidtranslation time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system pre-generates and stores query translation templates and mapping rules between different database languages (SQL, NoSQL, etc.) before actual query execution. This preliminary preparation enables rapid translation during runtime without manual intervention, resolving the contradiction between compatibility and time consumption.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary translation layer that sits between the client application and different database systems. This layer automatically translates queries between machine interpretable languages using pre-defined rules and mappings, eliminating manual translation efforts while ensuring compatibility across diverse database platforms.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If manual query translation is performed to ensure accuracy, then translation precision improves, but productivity decreases due to time-consuming processes

Engineering Contradiction:

Improvetranslation accuracyVSAvoidquery processing speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system replaces manual mechanical translation processes with an automated computational translation engine. This engine uses algorithmic rule-based translation and pre-computed mapping templates to accurately translate queries between different machine interpretable languages instantaneously, eliminating the trade-off between accuracy and speed.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The translation system dynamically adjusts translation parameters and selection of translation rules based on the specific query type, source database language, and target database language. This parameter-based approach ensures high translation accuracy while maintaining rapid processing speeds through automated rule application.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If conversational improvements are allowed in translation, then translation quality improves, but processing time increases beyond real-time requirements

Engineering Contradiction:

Improvetranslation qualityVSAvoidprocessing speed

Core Design Contradiction:

ReliabilityVSSpeed

Solution Approach 1:

The translation system segments queries into distinct components (SELECT clauses, WHERE conditions, JOIN operations, etc.) and applies specific translation rules to each segment independently. This segmentation enables parallel processing of query components, maintaining high translation quality through rule-based accuracy while achieving real-time processing speeds through concurrent execution.

Inventive Principle:

Principle #1Segmentation

4Adaptability or versatility

If manual conversion between database languages is performed, then compatibility is achieved, but error rates increase due to human factors

Engineering Contradiction:

Improvelanguage compatibilityVSAvoidtranslation accuracy

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The system implements self-service automated translation that performs query conversion between different machine interpretable languages without human intervention. The translation engine automatically handles syntax differences, data type mappings, and query structure transformations, eliminating human errors while ensuring compatibility across diverse database languages through consistent rule-based translation.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12298972B2System and method for recursive transliteration of machine interpretable languages

Publication Date: 2025.05.13 BANK OF AMERICA CORP

AI summary

Aspects of the disclosure relate to transliteration of machine interpretable languages. The computing platform may receive a query, formatted in a first format for execution on a first database. The computing platform may translate the query to a second format for execution on a second database by: 1) extracting non-essential parameters from the query to create a query key; 2) storing the non-essential parameters; 3) executing a lookup function on a query library to identify a translated query corresponding to the query key; 4) based on identifying that the query library includes portions of the query key rather than the query key, recursively identify the translated query by nesting the portions of the query key; and 5) input the non-essential parameters into the translated query to create an output query. The computing platform may execute the output query on the second database.