Key-Value Store to Relational Database Migration

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Solution Overview

Problem

Migrating data from an unstructured key-value store to a structured relational database is challenging due to unknown data organization, leading to errors and inefficiencies in previous techniques that require additional procedures and are prone to inaccuracies, especially when dealing with nested JSON objects or fields.

Innovation Solution

The system analyzes the key-value store in its native format to identify namespaces, kinds, and entities, generating a relational database model with schema-based mappings between key-value data and columns/rows, eliminating the need for nested JSON analysis and ensuring accurate data migration by directly converting data into correct columns and rows.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data is stored in an unstructured key-value store format, then data flexibility and schema-less storage are improved, but data migration to relational databases becomes problematic and error-prone

Engineering Contradiction:

Improvedata flexibilityVSAvoidmigration accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary analysis of the key-value store data to discover entities, properties, and relationships before migration. This preliminary structuring enables accurate mapping to relational database schemas, resolving the contradiction between maintaining unstructured flexibility and ensuring reliable migration.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary data model that serves as a bridge between the unstructured key-value store and the structured relational database. This intermediary representation captures the semantic meaning of data elements and their relationships, enabling accurate transformation while preserving data integrity.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If previous migration techniques are used to convert key-value store to relational model, then data migration is attempted, but additional procedures are required and errors are prone

Engineering Contradiction:

Improvemigration processVSAvoidmigration procedures

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs self-service by automatically discovering the data model from the key-value store through analysis of data patterns, entities, and relationships. This automated self-configuration eliminates the need for manual schema design and reduces migration complexity while maintaining productivity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent transforms the migration approach by changing the fundamental parameters from manual schema definition to automated data-driven schema discovery. This parameter change simplifies the migration process by letting the system adapt to the data characteristics rather than forcing data into pre-defined schemas.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If nested JSON objects or fields are analyzed in previous techniques, then data conversion is attempted, but inaccuracies occur due to unknown data organization

Engineering Contradiction:

Improvedata conversion accuracyVSAvoidmigration time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mechanical approach of parsing and analyzing nested JSON structures with a direct key-value store analysis method. By working with the native data format and using automated discovery algorithms, the system achieves accurate data conversion without the time-consuming JSON parsing process.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12189665B2Conversion and migration of key-value store to relational model

Publication Date: 2025.01.07 CORP ORACLE INT

AI summary

Systems, methods, and other embodiments associated with migrating key-value data to a relational database. A method comprises retrieving a namespace from a key-value store and querying the key-value store for a kind category associated with the namespace. The key-value store is accessed and data entities are retrieved that are associated with the kind category that is defined with the namespace identifier. Property names and associated property values are identified in the data entities. The method generates a relational database model including a table; assigns the namespace identifier as schema of the table and assigns the kind category as a table name; builds the table in the relational database model by defining a plurality of columns, wherein a column is defined for each different property name identified from the data entities; and migrates data from the data entities to rows in the table in the relational database model.