Cross-Platform Database Data Transfer via Intermediary Parsing
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Solution Overview
Problem
Traditional database management systems face complexity and inefficiency when transferring data across different platforms due to incompatibility of import and export utilities, requiring custom workarounds for data sharing and integration.
Innovation Solution
A method and system that utilize a data reader to parse and identify database objects and row-level data from a file generated by an export utility of one database platform, and a data loader to insert this data into a destination database on a different platform using dedicated data insertion threads, facilitating cross-platform data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional import and export utilities are used for cross-platform data transfer, then data can be transferred between databases, but the utilities are incompatible with other platforms increasing complexity and requiring custom workarounds
Solution Approach 1:
The patent introduces an intermediary data transfer system that reads export files from a source database platform and loads data into a destination database platform. This intermediary acts as a mediator between incompatible platforms, translating and transferring data without requiring custom workarounds for each platform pair.
Solution Approach 2:
The data transfer utility is designed to be universal and platform-agnostic, capable of working with multiple different database platforms. It can read from various export formats and load into different destination databases, making it adaptable across platforms without requiring platform-specific implementations.
2Reliability
If custom workarounds are implemented for cross-platform data transfer, then data transfer can be achieved, but the level of complexity and effort required increases significantly
Solution Approach 1:
The data transfer system performs self-service by automatically reading export files, parsing the data, and loading it into the destination database without requiring manual intervention or custom scripting. The system handles the entire data transfer process autonomously, reducing the effort required from users.
Solution Approach 2:
The system prepares for data transfer by first reading and parsing the export file structure before actual data loading begins. This preliminary action allows the system to understand the data format and plan the transfer process, making the actual data transfer more efficient and requiring less ongoing effort.
3Quantity of substance
If data is transferred using traditional methods, then data can be moved between platforms, but the transfer process is slow and inefficient
Solution Approach 1:
The data transfer system maintains continuous operation by reading data from the export file and loading it into the destination database in an uninterrupted flow. The system keeps both the data source and destination active simultaneously, maximizing productivity throughout the transfer process.
Solution Approach 2:
The system uses periodic batching to transfer data in efficient chunks, reading portions of the export file and loading them into the destination database in repeated cycles. This periodic action allows for optimized I/O operations and maintains high transfer speed while handling large volumes of data.
Data Source
AI summary
Methods and systems for transferring data across incompatible database platforms are provided. A method may include reading data from a database export file containing a representation of objects and data from a source database of a first database platform, where the file was generated by an export utility of the first database platform, has a format specific to the first database platform, and is stored outside of the source database. The data read from the file is parsed based on the format. At least one database table represented in the file is identified based on the parsing. Row-level data associated with the at least one database table is also identified based on the parsing. The row-level data is collected in a buffer and is then inserted into a destination database of a second database platform using at least one dedicated data insertion thread.