Programmatic Interfaces for Bulk Data Transfer
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Solution Overview
Problem
Existing data integration techniques require custom code development for each data store, making bulk data transfers between persistent data stores cumbersome, difficult to maintain, and not reusable, limiting their applicability in complex integration scenarios.
Innovation Solution
A system with programmatic source and target interfaces that abstract bulk data transfer operations, allowing extraction and loading of data between any data stores without the need for custom code, using a common specification to isolate specific details and enable transparent compatibility between sources and targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If custom code is developed for each data store to handle bulk data transfers, then data transfer functionality can be achieved, but development time and maintenance complexity increase significantly
Solution Approach 1:
The patent creates a universal data transfer system that can handle bulk data transfers between any data stores through a common interface architecture. The source interface and target interface definitions establish standardized methods (open, getNext, close) that work across different data store types, eliminating the need for custom code for each data store combination.
Solution Approach 2:
The patent introduces intermediate components including a data transfer manager, source interfaces, and target interfaces that mediate between the data transfer logic and specific data stores. These interfaces act as translators that convert universal transfer operations into data store-specific operations, reducing overall system complexity.
2Adaptability or versatility
If custom code is developed for each data store integration, then specific data store requirements can be met, but code reusability decreases
Solution Approach 1:
The interface definitions create universal source and target interfaces that can work with any data store type. The standardized methods (open, getNext, close) provide a common contract that enables code reusability across different data stores while maintaining adaptability to specific requirements through interface implementation.
Solution Approach 2:
The patent segments the data transfer system into distinct components: source interface definitions, target interface definitions, and transfer logic. This segmentation allows each component to be developed and reused independently, with the interface definitions serving as reusable templates that can be applied across multiple data store integrations.
3Productivity
If multiple custom code pieces are developed for extraction, transformation, and loading, then complete data transfer functionality is achieved, but maintenance difficulty increases
Solution Approach 1:
The patent merges the extraction, transformation, and loading functionalities into a unified data transfer framework. The source interface, target interface, and transfer manager work together as an integrated system with standardized interactions, reducing maintenance difficulty compared to separate custom code pieces while maintaining complete data transfer functionality.
4Productivity
If ETL tools are used for simple integration scenarios, then basic data transfer can be handled, but capability limitations prevent relief from development burdens
Solution Approach 1:
The patent extends basic ETL tool capabilities by creating a universal interface framework that supports complex integration scenarios. The standardized source and target interfaces can accommodate various data store types and transfer requirements, providing both the basic data transfer capability of ETL tools and the adaptability needed for complex scenarios.
Data Source
AI summary
In one embodiment, a system is provided for executing bulk data transfers between persistent data stores. Programmatic source interfaces are each associated with a source store, defined according to a source interface specification, and exposed during a transfer to enable extraction from its source store of data entities for loading into any selected target stores during the transfer. Programmatic target interfaces are each associated with a target store, defined according to a common target interface specification, and exposed during a transfer to enable loading into its target store of data entities extracted from any selected source stores during the transfer. Each programmatic interface: (1) provides to its store an abstraction of transfer operations such that custom code need not be developed in connection with its store to enable transfers between its store and any other particular stores; and (2) isolates specific details associated with its store such that custom code need not be developed in connection with the transfer operations to enable transfers between its store and any other particular stores.