Gateway-Mediated Uniform API Across Heterogeneous Data Stores
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Solution Overview
Problem
The complexity of integrating and accessing data across diverse data stores due to varying redundancy, accessibility, processing speed, and security requirements increases the difficulty of generic data browsing and writing, especially when multiple types of data stores are involved.
Innovation Solution
A scalable, resilient, and high-performance connectivity framework with a standardized Application Programming Interface (API) for disparate data systems, utilizing connectors and a gateway to manage communication and metadata retrieval, supported by a connector registry and cloud-native architecture for elastic scaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple types of data stores are used to meet diverse redundancy, accessibility, processing speed, and security requirements, then data storage flexibility and performance are improved, but the complexity of data integration and generic metadata browsing increases
Solution Approach 1:
The patent introduces a gateway as an intermediary component that sits between clients and multiple data stores. The gateway receives client requests, routes them to appropriate data stores, and returns results in a unified format. This mediator approach allows the system to support diverse data stores (improving adaptability) while shielding clients from the complexity of dealing with multiple data store types directly (reducing integration complexity).
Solution Approach 2:
The gateway is designed as a universal interface that can handle multiple types of data stores through a single standardized API. It provides multi-functional capabilities including metadata browsing, data writing, and routing to different data store types. This universality allows one component to serve multiple purposes and work with various data store types without requiring separate integration logic for each, thus resolving the contradiction between versatility and complexity.
2Productivity
If multiple types of data stores are used with different requirements, then data processing capabilities are improved, but the difficulty of writing data to any given data store increases
Solution Approach 1:
The gateway acts as an intermediary that abstracts the complexity of writing data to different data stores. Clients interact with the gateway through a standardized interface, and the gateway handles the translation and routing to appropriate data stores. This maintains high data processing capabilities across multiple store types while making data writing easy for clients through a unified interface.
Solution Approach 2:
The system segments the data writing function into two parts: a standardized client interface and data store-specific implementation logic. The gateway contains the segmentation logic, separating the ease of use (standardized interface) from the complexity (data store-specific requirements). This allows clients to write data easily without needing to understand the complexities of different data store formats and protocols.
3Ease of operation
If a standardized API is implemented across diverse data systems, then ease of operation and communication are improved, but the device complexity and infrastructure requirements increase
Solution Approach 1:
The gateway serves as the standardized API interface that clients interact with, providing ease of operation through consistent methods and data formats. The infrastructure complexity of supporting multiple data stores is contained within the gateway itself, not propagated to clients. This mediator approach allows a standardized API to be implemented without requiring each client to handle the underlying infrastructure complexity.
Solution Approach 2:
The patent merges multiple data store interfaces and protocols into a single unified gateway interface. Instead of requiring separate integration logic for each data store type, the gateway combines all data store interactions through one standardized entry point. This merging reduces the operational complexity for clients while maintaining support for diverse data stores behind the unified interface.
Data Source
AI summary
Systems and methods include reception of a first call to a first interface at a first connector associated with a first data system, the first call requesting to write first data to the first data system and conforming to a data model, conversion, at the first connector, of the first call to a first data model of the first data system, transmission of the converted first call from the first connector to the first data system, reception of a second call to the first interface at a second connector associated with a second data system, the second call requesting to write second data to the second data system and conforming to the data model, conversion, at the second connector, of the second call to a second data model of the second data system, and transmission of the converted second call from the second connector to the second data system.