Universal Data Model for Multi-Format Storage Optimization
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Solution Overview
Problem
Conventional database systems are limited by predefined schema and structures that do not optimize for data storage and retrieval, leading to inefficiencies due to tight coupling between data relationships and storage structures, making it difficult to handle diverse data formats and query optimizations.
Innovation Solution
The system employs a universal data model based on extended set theory for storing and processing data in various formats, using algebraic relations to optimize storage and access, allowing for adaptive data restructuring and parallel processing, thereby eliminating the need for prestructuring and database index structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional database systems use predefined schema and fixed storage structures, then data relationships are well-defined and manageable, but storage access efficiency deteriorates due to tight coupling between data relationships and storage structures
Solution Approach 1:
The patent segments the database system into multiple independent storage formats (relational, hierarchical, network, object-oriented) that can be accessed separately. Each format maintains its own optimization characteristics, allowing the system to choose the most efficient access path for different data relationships without being constrained by a single predefined schema.
Solution Approach 2:
The patent creates a universal data model that can represent data in multiple storage formats simultaneously. This multi-functional approach allows the same data to be stored and accessed in different formats depending on the query requirements, enabling both relational integrity and optimized access paths to coexist.
2Device complexity
If a single storage format is used for all data, then storage structure is simple and manageable, but the system cannot efficiently handle diverse data formats and query optimizations
Solution Approach 1:
The patent implements a universal data model that can represent and access data in multiple storage formats (relational, hierarchical, network, object-oriented) within a single system. This allows the database to handle diverse data formats and optimize queries based on the specific format being accessed, without requiring separate database systems for each format.
Solution Approach 2:
The patent introduces an intermediary layer (the universal data model and query optimization system) that translates between different storage formats and the user's query requirements. This mediator handles the complexity of multiple formats internally while presenting a unified interface to users, maintaining simplicity at the user level while providing versatility internally.
3Productivity
If data is stored in multiple formats with loose coupling, then query flexibility and optimization improve, but the system complexity increases due to multiple storage formats and access methods
Solution Approach 1:
The patent uses the universal data model as an intermediary that manages multiple storage formats. This mediator handles the complexity of coordinating between different formats, translating queries into appropriate access patterns, and managing data consistency across formats, thereby improving query efficiency without exposing the full system complexity to users.
Solution Approach 2:
The patent implements dynamic query optimization that adapts to the specific data formats and access patterns being used. The system can dynamically select the most efficient storage format and access method for each query based on current conditions, allowing high productivity while managing complexity through adaptive rather than static structures.
4Speed
If traditional database indexing structures are used, then data retrieval is optimized for predefined relationships, but the system cannot efficiently process dynamically changing data and diverse formats
Solution Approach 1:
The patent replaces static indexing structures with dynamic access methods that can adapt to changing data and query requirements. The universal data model allows the system to dynamically select appropriate access paths for different storage formats and update strategies, maintaining high retrieval speeds while handling dynamically changing data and diverse formats without being constrained by predefined indexes.
Data Source
AI summary
Systems and methods for storing and accessing data. Algebraic relations may be composed that each define a result equal to a requested data set. The algebraic relations may reference other data sets in storage. Some of the data sets may contain the same logical data stored in different physical formats and/or in different locations in the data store. One of the algebraic relations may be selected for use in providing the requested data set based, at least in part, on the physical format and/or locations of the data sets referenced in the algebraic relations. In other examples, algebraic relations may be selected based, at least in part, on the speed and available bandwidth of the channel(s) used to retrieve data sets referenced in the algebraic relation. Functions may be used to calculate the algebraic relation using the data sets retrieved from storage. The functions may be format specific based on the physical formats of the data sets provided as operands to the functions.