Connection-Detail Buffering Client for Fast Cache Invalidation
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Solution Overview
Problem
Modern organizations face challenges in seamlessly integrating data across diverse data stores due to complexity, scalability issues in middleware, and security concerns related to user credentials and network details, leading to inefficient data integration.
Innovation Solution
A scalable, resilient, and extensible framework is implemented using connectors, a gateway, and a connector registry that manages connection details through in-memory buffers and secure storage, ensuring efficient and secure data integration across disparate data systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored across multiple diverse data stores to meet different requirements (redundancy, accessibility, processing speed, security), then data security and performance are improved, but the complexity of data integration increases
Solution Approach 1:
The patent introduces a connector as an intermediary component that manages connections between applications and diverse data stores. The connector handles authentication, credential management, and communication protocols, isolating the complexity of integrating multiple data stores from the application layer. This mediator approach allows secure access to multiple data stores without requiring the application to directly manage each connection's complexity.
Solution Approach 2:
The connector is designed as a universal component that can work with multiple types of data stores (databases, file storages, cloud services, third-party vendors) through a standardized interface. This multi-functionality allows the same connector architecture to handle different data store types, reducing integration complexity while maintaining security and performance requirements for each specific data store.
2Ease of operation
If existing middleware is used to route communication between application and data stores, then data integration is enabled, but scalability and extensibility are limited
Solution Approach 1:
The patent segments the middleware functionality into distinct, independent components: the connector, the gateway, and the data store adapters. This segmentation allows each component to be developed, deployed, and scaled independently. The connector can be extended to support new data store types without affecting the core gateway, enabling better scalability and adaptability compared to monolithic middleware solutions.
Solution Approach 2:
The connector implementation is designed to be dynamic and configurable, allowing it to adapt to different data store types and communication requirements. The connector can load different adapters dynamically based on the target data store, enabling the system to scale and extend functionality without redeploying the entire middleware stack.
3Productivity
If user credentials and network details are stored for data store connections, then connection efficiency is improved, but security risks increase due to credential persistence
Solution Approach 1:
The connector acts as a secure intermediary that manages credential storage and retrieval. Instead of applications directly storing and managing sensitive credentials, the connector provides a controlled interface for credential access. This intermediary layer implements security protocols, encryption, and access controls, enabling efficient credential reuse while mitigating security risks through centralized security management.
4Reliability
If connection details are frequently updated to maintain freshness and security, then security is improved, but connection stability and performance deteriorate
Solution Approach 1:
The connector implements local caching of connection details with differentiated update strategies for different components. Frequently changing credentials (like access tokens) are cached with short expiration times and automatically refreshed, while stable connection parameters (like endpoint URLs) are cached longer. This local quality approach maintains security through frequent updates of sensitive data while preserving connection performance by minimizing reconnection events.
Data Source
AI summary
Systems and methods include reception of a first request from a first instance of a first connector service, the first request specifying a first connection identifier, determination that first connection details associated with the first connection identifier are stored in a local memory buffer, transmission of the first connection details from the local memory buffer to the first instance in response to the determination that the first connection details are stored in the volatile memory buffer, and reception of a notification indicating that the first connection details have changed. In response to the notification, the notification is stored in a persistent storage, the first connection details stored in the local memory buffer are invalidated, and an instruction is transmitted to the first instance of the first connector service to invalidate the first connection details stored at the first instance.