Data Retrieval Interface with Intelligent Routing
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Solution Overview
Problem
The variability in hardware locations and network conditions makes it challenging for applications to efficiently access and retrieve data from diverse data sources, as they must adapt to changing latency, cost, and connectivity across different environments.
Innovation Solution
A standardized data retrieval interface is implemented, which uses a routing layer to select data sources based on latency, cost, and connectivity, and provides a data abstraction layer to manage formatting and connections, allowing applications to query data using a unified schema definition language regardless of the operating environment or programming language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If applications directly access data from multiple diverse data sources in different hardware locations, then data accessibility is improved, but system complexity and difficulty of managing varying network conditions increases
Solution Approach 1:
The patent introduces a data retrieval interface as an intermediary layer between applications and multiple data sources. This interface abstracts the complexity of accessing data from diverse hardware locations and network environments, allowing applications to query data uniformly without directly managing the underlying complexity of different data source connections and network conditions.
2Productivity
If applications implement custom data access logic for each data source, then data retrieval efficiency is improved, but ease of operation and development time worsens
Solution Approach 1:
The data retrieval interface provides a universal query mechanism that works across multiple data sources with different formats and locations. Instead of requiring applications to implement custom access logic for each data source, the interface handles diverse data source connections, formatting, and retrieval operations through a single unified approach, improving ease of operation while maintaining efficient data retrieval.
3Adaptability or versatility
If data is stored remotely in cloud environments, then data centralization and accessibility are improved, but network latency and connectivity dependencies increase
Solution Approach 1:
The system segments data storage across multiple locations including local and remote data sources. The data retrieval interface can query both local data sources (reducing latency) and remote cloud data sources (providing centralization), selecting appropriate sources based on the specific data access needs. This segmentation allows the system to maintain data centralization benefits while minimizing network latency by accessing local sources when possible.
Data Source
AI summary
A system comprising one or more computers implements a data retrieval interface. The data retrieval interface provides a unified schema definition language for data queries. Also the data retrieval interface implements a routing layer that applies default or custom prioritization parameters to select a data source from which to obtain data requested in a query from an application. The data retrieval interface may take into consideration connectivity, latency, costs, or other user specified parameters when selecting a data source and/or when selecting connection path to a selected data source to be used to obtain data in response to a query.