Multi-Model NoSQL Database Structure for Distributed Data
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Solution Overview
Problem
Current NoSQL database structures do not support all three key-value pair (wide-column), object/document, and graph data models within a single database, limiting scalability and flexibility.
Innovation Solution
A multi-model NoSQL database structure that utilizes a wide-column store core to support wide-column, document, and graph data models, enabling documents with unique keys to be stored with dynamic columns and graph edges defined as tuples of source, target, tag, and value, allowing for flexible schema-less data management and full-text searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single NoSQL database structure supports only one data model (key-value, document, or graph), then the database structure can be optimized for that specific model, but the system lacks versatility and requires multiple separate databases to support different data models
Solution Approach 1:
The patent implements a universal NoSQL database structure that can support multiple data models (key-value, document, and graph) within a single system. The wide-column store serves as a common foundation that can represent different data models through flexible schema design, allowing the same underlying structure to perform multiple functions and eliminate the need for separate specialized databases
Solution Approach 2:
The patent combines elements of different data models into a composite structure. The wide-column store integrates key-value pairs, document fields, and graph relationships into a unified framework, where columns can represent both simple key-value data and complex nested document structures, while also supporting graph edges through appropriate column family organization
2Adaptability or versatility
If a NoSQL database uses a fixed schema with pre-defined fields, then data retrieval can be optimized for known structures, but users cannot dynamically add or delete fields without altering the schema
Solution Approach 1:
The patent implements dynamic schemas in the wide-column store where columns can be added, removed, or modified at runtime without requiring pre-definition or schema alteration procedures. The flexible column-family structure allows fields to be dynamically created based on application needs, with the underlying storage adapting to accommodate new column names and types without disrupting existing data or requiring system reconfiguration
3Speed
If a database stores graph edges as separate entities, then graph operations can be optimized, but the overall storage structure becomes more complex and requires additional index lookups
Solution Approach 1:
The patent merges graph edge storage with the document rows in the wide-column store. Graph edges are stored as columns within the same row structure as vertex data, eliminating the need for separate graph storage entities. This integration allows graph operations to be performed directly on the unified data structure without requiring additional index lookups or separate storage access paths
Data Source
AI summary
Aspects define NoSQL database structures that support wide-column, document, and graph data models. Documents are defined with different, unique keys and stored to different rows in a wide-column store by mapping their respective, unique keys directly to different row keys. Columns are defined for the document rows as including pairs of names and values, each column field having a different column name. Graph edges are defined as a function of relationships between a first source document and a second of the documents as tuples of first source document keys, second document keys as targets, tags as labels of relationships, and values of objects associated with the relationships. The graph edges are stored as graph columns within rows of the first source documents with names that are different from names of other columns within the first source document rows.