Unified Data Retrieval Operator for Multi-Modal Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional data storage systems struggle with querying across multiple data types, leading to time-consuming processes due to the volume, complexity, and multiple modalities of data, particularly with large datasets like geo-spatial data.
Innovation Solution
A system comprising a retrieval operator, user-defined function (UDF) operator, and artificial intelligence (AI) operator, in communication with an interface layer and multiple shards of a database, to simultaneously search and retrieve various types of data, including structured, semi-structured, and unstructured data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional separate data storage by data type is used, then data storage organization is simple, but query efficiency across multiple data types deteriorates
Solution Approach 1:
The patent merges multiple separate data storage systems (relational databases, graph databases, document databases, key-value stores, and object storage) into a unified data storage system. This consolidation allows queries to access all data types simultaneously through a single interface, dramatically improving query efficiency across structured, semi-structured, and unstructured data while maintaining organized storage through specialized database engines for each data type.
2Adaptability or versatility
If multiple database types are used to handle different data types, then data type coverage is comprehensive, but query time increases
Solution Approach 1:
The unified data storage system implements a universal query interface that can handle multiple data types (structured, semi-structured, unstructured) through a single system. The system incorporates specialized database engines for different data types while providing a unified access point, allowing comprehensive data type coverage without requiring separate query operations for each data type, thus reducing overall query time.
Solution Approach 2:
The system pre-processes and indexes data from multiple sources into a unified structure with standardized schemas. By organizing data in advance with consistent indexing and metadata structures, the system enables faster retrieval operations without requiring complex real-time data transformation during queries, thereby reducing query time while maintaining comprehensive data type support.
3Measurement precision
If traditional query systems are used, then system simplicity is maintained, but search accuracy across multiple modalities deteriorates
Solution Approach 1:
The patent introduces an intermediary layer consisting of unified data schemas, standardized indexing mechanisms, and a universal query interface that sits between the diverse data sources and the query system. This intermediary layer translates various data modalities into a common format, enabling accurate cross-modal searches while abstracting the underlying system complexity from users and applications.
Data Source
AI summary
Systems and methods disclosed herein may include a plurality of operators to search and retrieve various types of data in a result set, simultaneously. The operators may include a retrieval operator, user defined function (UDF) operator, and artificial intelligence (AI) operator in communication with an interface layer and multiple shards of a database for generating the result set.