Universal Data Store System for Cross-Database Schema Mapping
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Solution Overview
Problem
Users face challenges when switching between different types of databases, as data transfer is time-consuming and prone to errors, requiring complex proprietary software and new command sets, especially when moving from SQL to non-SQL databases or between databases with varying schemas and syntax.
Innovation Solution
A universal data store system that manages data across multiple specialized data stores using a universal schema, plug-ins, and transformers to facilitate CRUD operations, data transformations, and trigger execution, allowing for seamless interaction and data transfer between different database types without the need for users to learn new command sets or proprietary languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is copied from one database to another database with different schema and syntax, then data transfer capability is achieved, but time consumption and error rate increase significantly
Solution Approach 1:
The patent introduces a mediator layer (data transfer service, schema mapping service) that sits between the source and target databases. This mediator automatically maps data from the source schema to the target schema, handles syntax differences, and manages the transfer process, thereby reducing manual intervention time and error rates while maintaining adaptability across different database types.
Solution Approach 2:
The patent creates a universal data transfer framework that can handle multiple database types (SQL, non-SQL, different schemas) through a single unified interface. The schema mapping service and data transfer service are designed to be database-agnostic, allowing the same system to adapt to various target databases without requiring separate custom software for each database type, thus improving efficiency.
2Reliability
If complex proprietary software is developed to copy data between databases with different schemas, then data transfer accuracy is improved, but device complexity and development effort increase
Solution Approach 1:
The patent implements a universal data transfer system with standardized services (data transfer service, schema mapping service) that can handle multiple database types through a single framework. This unified approach maintains data transfer accuracy across different database schemas without requiring separate complex proprietary software for each database combination, thereby reducing overall software complexity while preserving reliability.
3Adaptability or versatility
If users switch to a different database type, then new features and capabilities are accessed, but learning curve and operational complexity increase
Solution Approach 1:
The patent introduces an intermediary layer (universal database interface, data transfer service) that shields users from the complexities of different database types. Users interact with a standardized interface while the intermediary handles the translation and adaptation to the specific database backend, allowing users to access diverse database features without needing to learn multiple command sets or operational procedures.
4Adaptability or versatility
If data is transferred between databases with different schemas, then database flexibility is improved, but data integrity and compatibility are compromised
Solution Approach 1:
The patent employs a schema mapping service as an intermediary that systematically maps source schema elements to target schema elements, preserving data integrity during transitions between different database schemas. The service handles type conversions, null value mappings, and constraint validations, ensuring that data remains accurate and compatible even when transferring between databases with fundamentally different schema structures.
Data Source
AI summary
In an embodiment, a method comprises receiving an input defining organization of one or more universal data elements; generating a universal schema that defines organization of the one or more universal data elements based on the input; associating the universal schema with a specialized plug-in, wherein the specialized plug-in maps the one or more universal data elements with data elements in one or more specialized databases maintained by a specialized data store; receiving, from a computer, a request to receive data stored in the specialized data store and comprising parameters based on the universal schema; transforming the request using the specialized plug-in to produce a specialized query; sending the specialized query to the specialized data store to execute the specialized query; receiving a specialized result set from the specialized data store; sending, to the computer, a result set based on specialized result set.