SQL-Driven Distributed Operating System for Heterogeneous Data Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems face challenges in accessing, analyzing, and combining data from diverse sources such as relational and NoSQL databases, files, and media objects without requiring data importation into a centralized system, and they often lack the ability to perform complex operations like ETL processes and ad-hoc queries efficiently.
Innovation Solution
The SQL-driven distributed operating system enables concurrent processing and access of data from various sources, including SQL and NoSQL databases, files, and media objects, using Structured Query Language (SQL) queries, allowing for operations like ETL processes, data joining, and ad-hoc queries without data importation, and optimizing performance through techniques like JIT compilation and dynamic resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in different types of databases and files with different formats, then data diversity and storage flexibility are improved, but data compatibility and accessibility deteriorate
Solution Approach 1:
The patent introduces SQL as an intermediary language that mediates between diverse data sources (relational databases, NoSQL databases, files, media objects) and the user/query system. SQL serves as a universal interface that translates various data formats and storage types into a common queryable format, enabling seamless access without requiring data importation or format conversion.
Solution Approach 2:
The system implements a universal SQL interface that can access and query multiple types of data sources simultaneously - relational databases, NoSQL databases, text files, log files, document files, image files, audio files, video files, spreadsheets, information sources, and information sinks. This multi-functional capability allows a single SQL query to operate across heterogeneous data types without requiring separate access mechanisms for each source.
2Reliability
If data is segregated in different silos managed by different teams, then data security and team autonomy are improved, but data integration and analysis capability deteriorate
Solution Approach 1:
The system maintains segmentation of data into different silos managed by different teams, preserving data security and autonomy. Each data source remains independently managed with its own access controls and team responsibilities. The SQL interface enables integration without physical consolidation, allowing segmented data to be queried together while maintaining organizational boundaries and security protocols.
3Productivity
If conventional systems import data into centralized systems for analysis, then data processing capability is improved, but system complexity and data transfer overhead deteriorate
Solution Approach 1:
The patent extracts the data importation step from the processing workflow entirely. Instead of importing data into a centralized system for analysis, the system extracts only the necessary query operations and executes them directly at the data source locations. This eliminates the overhead of data transfer, storage, and management in centralized systems while maintaining full processing capability.
4Adaptability or versatility
If ETL processes are performed on diverse data sources, then data transformation capability is improved, but processing time and resource consumption deteriorate
Solution Approach 1:
The system performs preliminary actions by establishing SQL connectivity and schemas for diverse data sources in advance. Once the SQL interface is configured for a data source, subsequent queries can execute directly without requiring ETL transformation steps. The preliminary setup enables fast, direct querying that eliminates the time-consuming data extraction, transformation, and loading processes.
Data Source
AI summary
Various embodiments can include systems, methods, and non-transitory computer readable media configured to receive at least one operation to be performed using (i) first data that is managed by a first computing system and (ii) second data that is managed by a second computing system, the operation being received through an interface provided by the computing system, and wherein the operation is based at least in part on a Structured Query Language (SQL). At least one optimization can be performed based at least in part on the operation. The operation can be executed using at least the first data and the second data. A result generated can be provided upon executing the operation through the interface provided by the computing system. The computing system, the first computing system, and the second computing system are each able to concurrently process, access, and create at least a portion of the generated result.