Automatic Data Translation Module for Database Storage Optimization
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Solution Overview
Problem
Software applications face challenges in efficiently translating and storing data across different formats, leading to increased complexity and storage inefficiencies, particularly with IP addresses which require redundant storage and inefficient querying due to format inconsistencies.
Innovation Solution
An automatic data translation module (ADTM) is integrated into the database API, enabling transparent data format conversion between applications, reducing the need for manual format checking and conversions, and optimizing storage by translating IP addresses between textual and binary formats as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple formats for different applications, then each application can access data in its preferred format, but storage space is wasted due to redundant data storage
Solution Approach 1:
The patent introduces a database abstraction layer as an intermediary between applications and the underlying database storage. This layer automatically translates and converts data between different formats as it passes through, allowing applications to access data in their preferred formats without requiring the actual data to be stored in multiple formats. The conversion happens transparently during data access operations, eliminating redundant storage while maintaining format compatibility.
2Reliability
If applications perform manual data format checking and conversion, then data can be accessed in the correct format, but application complexity increases
Solution Approach 1:
The database abstraction layer performs automatic self-service by detecting the required data format based on the application's needs and automatically converting the data to the appropriate format without requiring manual intervention from the application. The system handles format checking, validation, and conversion transparently within the abstraction layer itself, freeing applications from these complex operations.
Solution Approach 2:
The abstraction layer acts as a mediator that intercepts data access requests, performs the necessary format checking and conversion operations, and returns the data in the correct format to the application. This intermediary handles all format-related complexity, allowing applications to work with simplified interfaces while maintaining data format correctness.
3Ease of operation
If IP addresses are stored in textual format for human readability, then logging is more readable, but storage efficiency and querying performance deteriorate
Solution Approach 1:
The patent applies different data formats to different contexts or locations within the system. IP addresses are stored in binary format in the database for efficient storage and querying, while the database abstraction layer automatically converts them to textual format when needed for logging and display purposes. This local quality approach allows each context to use the most appropriate format without compromising overall system efficiency.
Data Source
AI summary
Techniques are disclosed for automatic data translation in computing systems. Certain techniques are disclosed herein that enable applications to utilize data in optimal formats specific to each application in an effectively transparent manner, removing the burden to perform data format or type checking, conversions, etc. An automatic data translation module (ADTM) is implemented that automatically translates data as it passes between certain applications. In some embodiments, the ADTM receives a first particular format of data from a first application and automatically/transparently converts the first particular format of data into another representation of the same data, but in a second format utilized by a recipient application. The ADTM may be configured as part of a database application programming interface (API), and can translate textual versions of IP addresses into binary representations for efficient database storage, and translate returned binary representations back into textual representations for convenience and enhanced trace functionalities.