Metadata Hub for Database Object Model Conversion
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Solution Overview
Problem
The increasing complexity of managing metadata models in large databases, where thousands of table types and billions of records interact, leads to challenges in maintaining data context and integrity due to varying metadata definitions and software versions across different entities.
Innovation Solution
A central metadata hub is introduced to store, retrieve, and compare metadata models, converting them between formats as needed, and allowing for the identification of related models and comparison of versions, independent of specific applications, to ensure data consistency and compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If metadata models are stored in multiple formats across different entities, then each entity can use its preferred format and version, but data consistency and integrity deteriorate due to varying definitions and software versions
Solution Approach 1:
The patent introduces a metadata hub as an intermediary system that receives metadata models from multiple entities in different formats, normalizes them to a standard internal representation, and distributes the standardized metadata back to requesting entities. This mediator architecture enables format compatibility while maintaining data consistency through centralized control and validation rules.
2Reliability
If a centralized metadata repository is implemented to ensure data consistency, then data integrity improves, but system complexity increases due to the need for format conversion and version management
Solution Approach 1:
The metadata hub architecture segments the system into distinct functional modules: a reception module for receiving metadata in various formats, a normalization module for converting to standard format, a storage module for the centralized repository, and a distribution module for delivering metadata to entities. This segmentation manages complexity by localizing conversion logic within specific modules rather than distributing it throughout the entire system.
Solution Approach 2:
The system performs preliminary normalization and validation of metadata models when they are first received and stored in the centralized repository, before any entity requests them. This preliminary action ensures data integrity is established upfront, reducing the need for complex validation logic at each access point and simplifying the overall system architecture.
3Adaptability or versatility
If metadata models are converted between formats in the centralized hub, then compatibility across entities improves, but processing time increases due to conversion operations
Solution Approach 1:
The metadata hub performs format conversion and normalization as a preliminary action when metadata models are first received and stored in the centralized repository. By converting all incoming metadata to the standard internal format upfront, the system eliminates the need for repeated conversion operations when entities request metadata, significantly reducing processing time for subsequent access operations.
Data Source
AI summary
Techniques and solutions are described for storing and processing metadata models using a metadata hub that can be accessed by a plurality of computing systems. The metadata hub can receive requests to retrieve or store metadata models. The metadata models can be converted between first and second formats. In some cases, the second format can be a relational format, such as a representation of a metadata model as one or more records in one or more database tables. The metadata hub can be used to compare metadata models, including comparing a metadata model provided by a client system with one or more metadata models stored in a repository maintained by the metadata hub. In at least some cases, the metadata model provided by the client system is not stored. The repository can be queried to find related metadata models, or to find metadata models meeting specified search criteria.