Unified Database Interface with AI Command Translation
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Solution Overview
Problem
Current database management systems require database administrators to learn multiple management systems for different types of databases, leading to inefficiencies such as the inability to view the status of all databases in a single interface, the need to send database-specific commands, and longer times to obtain results.
Innovation Solution
A software application that uses artificial intelligence to receive input commands, predict necessary commands, convert plain English commands into database-specific commands, and execute these commands across multiple databases from different vendors, providing a unified interface for management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple database management systems are used to manage different types of databases, then each database can be managed with its native capabilities, but the complexity of the management system increases and administrators must learn multiple interfaces
Solution Approach 1:
The patent implements a universal database management system that can manage multiple types of databases (Oracle, MongoDB, Cassandra, etc.) through a single unified interface. The system translates user commands into database-specific commands, allowing administrators to interact with all databases using one consistent management tool rather than requiring separate native management systems for each database type.
Solution Approach 2:
The patent introduces a command translation layer that acts as an intermediary between the unified user interface and the various database-specific command interfaces. This translation mechanism converts generic user commands into the appropriate database-specific syntax, enabling seamless communication with different database types without requiring users to learn multiple command languages.
2Reliability
If database-specific commands are sent to each database type, then precise control over each database is achieved, but the time required to execute commands and merge results increases
Solution Approach 1:
The patent pre-configures translation rules and command mappings for different database types during system initialization or setup phases. By preparing the translation framework in advance, the system can quickly translate and execute commands without performing complex real-time analysis, thereby reducing execution time while maintaining accuracy.
Solution Approach 2:
The patent dynamically adjusts command parameters and translation strategies based on the target database type. The system identifies the specific database being addressed and modifies the command structure accordingly, optimizing execution efficiency for each database type while maintaining a unified user interface.
3Loss of information
If multiple management systems are used to view database status, then comprehensive monitoring is possible, but the ability to view all databases in a single interface is lost
Solution Approach 1:
The patent consolidates status monitoring capabilities from multiple database management systems into a single unified interface. The system aggregates status information from various databases (Oracle, MongoDB, Cassandra, etc.) and presents them together in one coherent view, allowing administrators to monitor all databases simultaneously without switching between multiple management tools.
Solution Approach 2:
The unified management interface provides universal monitoring capabilities that work across all supported database types. The system displays comprehensive status information including health metrics, performance data, and operational states for all connected databases through a single consistent interface, eliminating the need to access separate management systems for status viewing.
Data Source
AI summary
In some aspects, a software application receives input including at least a portion of a command and determines, using an artificial intelligence algorithm and based on the input and historical data, predicted commands. The software application receives a selection of one of the predicted commands, determines databases affected by the selected commands, determines database vendors associated with each affected database, converts the selected commands into database specific commands, and sends the database specific commands to the affected databases for execution. For example, the software application may send first database specific commands to a first database associated with a first database vendor and may send second database specific commands to a second database associated with a second database vendor.


