Multimodal Database Unified Data Layer Latency Reduction
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Solution Overview
Problem
Conventional monolithic database systems face high latency, computational burdens, and errors due to their architecture, which limits real-time analytics and scalability, and requires schema-based queries that become obsolete with data changes.
Innovation Solution
A multimodal and distributed database system with a unified data layer and query engine that maps various data storage mechanisms to a common abstraction, allowing domain-based queries without schema requirements, enabling real-time data extraction and synchronization across heterogeneous databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If monolithic architecture is used, then system simplicity is maintained, but latency increases and real-time analytics become impossible
Solution Approach 1:
The patent divides the monolithic analytical system into multiple independent microservices, each responsible for specific data domains. This segmentation allows parallel processing of queries across different domains, eliminating the sequential processing bottleneck in monolithic systems and significantly reducing latency while maintaining overall system simplicity through standardized communication protocols.
2Measurement precision
If schema-based queries are used, then query precision is maintained, but adaptability to data changes deteriorates
Solution Approach 1:
The patent introduces a unified data layer as an intermediary between the query engine and underlying databases. This layer provides a consistent data model that abstracts the complexity of multiple database schemas, allowing queries to be written once and executed across heterogeneous systems without requiring schema knowledge or manual query adaptation when data structures change.
3Productivity
If distributed architecture is implemented, then scalability is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal query engine that can execute queries across multiple data domains and database types through a unified interface. This multi-functional approach eliminates the need for separate query handling mechanisms for each database, reducing operational complexity while enabling scalable distribution of data and queries across the system.
Data Source
AI summary
Embodiments of the invention are directed to a system, method, or computer program product for multimodal and distributed database system structured for dynamic latency reduction. In this regard, the invention comprises a unified data layer structured to map a plurality of data storage mechanisms to a common abstraction and a query engine structured for heterogenous domain based data extraction without requiring input of schema-based queries. In some embodiments, the invention comprises determining (i) one or more data components and (ii) one or more associated data domains associated with the first domain-based query by parsing the user input based on derived metadata from data dictionaries associated with a unified data layer system component. Moreover, the invention is configured to extract stored data from each of a plurality of databases based on the associated one or more data domains.