SQL Entity-Relationship Model Extension for Data Fragmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing database technologies face fragmentation and inefficiency due to the inability to share information across higher-level entity-relationship models, leading to redundant information provision and increased overhead, particularly for developers who are not SQL experts.
Innovation Solution
Extending the relational model and language of standard SQL to recognize features of higher-level entity-relationship models by incorporating entities and associations, allowing for a more semantic and intuitive data model that can share information across different applications and stacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If higher-level entity-relationship models are introduced to provide semantics and ease consumption, then data models become more comprehensible and user-friendly, but information cannot be shared across different models and stacks, leading to fragmentation
Solution Approach 1:
The patent introduces a universal annotation framework that can be applied across different entity-relationship models (OData EDM, RDL, JPA, etc.). The annotation syntax and semantics are designed to be model-agnostic, allowing the same annotation structure to work with multiple ERM types. This enables information to be shared across previously incompatible stacks while maintaining the benefits of higher-level models.
Solution Approach 2:
The patent introduces annotations as an intermediary layer between different entity-relationship models. These annotations serve as a common language that can be attached to entities and associations regardless of the underlying ERM type. The annotation processor acts as a mediator that interprets these annotations across different model stacks, enabling information sharing without requiring direct compatibility between models.
2Adaptability or versatility
If redundant information is provided to cope with fragmentation between applications, then information can be accessed by individual applications, but overhead is undesirably increased
Solution Approach 1:
The patent merges the information representation across different applications by introducing a common annotation framework. Instead of each application maintaining separate redundant information, the annotations provide a unified representation that can be consumed by multiple applications. This combining approach reduces the total quantity of information stored while maintaining accessibility for all applications.
Solution Approach 2:
The annotation framework is designed to be universally consumable by multiple applications and tools. A single set of annotations can serve multiple purposes: providing semantics for OData services, supporting RDL models, enabling JPA mappings, and more. This multi-functionality eliminates the need for redundant information provision while maintaining broad accessibility.
3Reliability
If standard SQL is used for database operations, then the relational model is well-supported, but developers who are not SQL experts face increased complexity and reduced productivity
Solution Approach 1:
The patent introduces annotations as an intermediary layer between the developer and standard SQL. Developers work with annotated entity-relationship models that are more intuitive and easier to understand, while the annotation processor automatically translates these annotations into the appropriate SQL operations. This intermediary approach maintains the reliability of SQL while improving developer productivity by eliminating the need for expert SQL knowledge.
Data Source
AI summary
Embodiments extend the relational model and language of standard SQL, to recognize features of higher level entity-relationship models (ERMs). SQL extensions implemented in the data design language (DDL) incorporate Entities (and Views) having custom-defined/semantic structure, rather than being limited to primitive types (e.g. flat tables as in standard SQL). Entities are defined similar to structured types with an underlying persistency, but with a uniquely identifying leading key. In DDL, these entities are combined with associations in the data model. The associations of the extended SQL reflect relationships between entities in the ERM. Associations are specified by adding an element to a source entity, with an association type pointing to a target entity. This may be complemented by providing optional information (e.g., cardinality, keys, filter conditions), up to a complete JOIN condition. In the query language (QL), JOINs may be replaced by the use of simple path expressions.