Algebraic Relation Optimizer for Data Storage and Retrieval
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Solution Overview
Problem
Conventional database systems are limited by predefined schema and structures that do not optimize data storage and retrieval, leading to inefficiencies in processing and accessing data, especially when dealing with diverse data formats like CSV and XML.
Innovation Solution
The implementation of a system that uses algebraic relations to optimize data storage and retrieval by creating a universal data model based on extended set theory, allowing for efficient processing and translation between different data formats without prestructuring, and utilizing parallel processing and distributed storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data is stored using predetermined schema with predefined relationships, then data structure is organized and accessible, but the schema cannot capture the original structure of data and is not optimized for actual data provision and query patterns
Solution Approach 1:
The patent implements dynamic schema evolution by allowing the database schema to automatically adapt and transform based on actual query patterns and data access behaviors. The system monitors how data is provisioned and queried, then dynamically restructures the schema to optimize these operations, making the schema flexible rather than static.
Solution Approach 2:
The system changes structural parameters of the database by transforming data between different logical structures (relational, hierarchical, network) and physical storage formats. This allows the same data to be accessed through multiple structural representations optimized for different query types without requiring a fixed predetermined schema.
2Productivity
If conventional database structures with predefined relationships are used, then data can be stored systematically, but query processing requires multiple storage accesses resulting in significant inefficiencies
Solution Approach 1:
The patent pre-calculates and stores intermediate query results and data transformations in advance. When a query is executed, the system retrieves pre-computed results rather than performing multiple sequential storage accesses, significantly reducing query processing time while maintaining systematic data organization.
Solution Approach 2:
The system introduces intermediate data structures and caching layers between the physical storage and query processing. These intermediaries hold pre-processed data in optimized formats, allowing queries to be answered quickly without directly accessing multiple storage locations sequentially.
3Reliability
If tight coupling between relationships and database structure is maintained, then data integrity is preserved, but it becomes difficult to efficiently capture, translate and process data in various different formats
Solution Approach 1:
The patent implements a universal data model that can represent data in multiple formats (relational, hierarchical, network, semi-structured) within a single unified framework. This universal structure maintains data integrity through consistent algebraic relationships while being versatile enough to efficiently capture and process diverse data formats without requiring format-specific processing paths.
Data Source
AI summary
Systems and methods for storing and accessing data. A relation store may be used to store algebraic relations between data sets. Alternative collections of algebraic relations may be generated and evaluated to determine an optimized collection of algebraic relations to use in calculating and providing a requested data set. Optimization criteria may be based on an estimate of the amount of data required to be transferred and/or the amount of time required to transfer data sets from storage in order to calculate the collection of algebraic relations. The optimization criteria may distinguish among equivalent data sets containing the same logical data in different physical formats or in different locations. The optimization may be performed using the algebraic relations rather than retrieving underlying data sets from storage. As a result, optimization may be performed at processor speeds to minimize the amount of time required for data to be retrieved.