Connector Registry and Gateway for Scalable Multi-Store Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern organizations face challenges in seamlessly integrating data across diverse data stores due to the complexity of configuring applications to connect with various data systems, exacerbated by poor scalability and extensibility of existing middleware.
Innovation Solution
A scalable, resilient, and extensible connectivity framework is implemented using connectors and a connector registry that supports multiple data systems, enabling elastic scaling and efficient routing through a gateway and registry system, utilizing gRPC and Protocol Buffers for communication and Apache Arrow for data format, with connectors as microservices on Kubernetes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diverse data stores are used to meet different data requirements, then data storage flexibility and suitability are improved, but data integration complexity increases
Solution Approach 1:
The patent introduces a gateway as an intermediary component that mediates between applications and diverse data stores. The gateway receives data access requests from applications, determines the appropriate data store and connector, and routes requests accordingly. This intermediary layer abstracts the complexity of multiple data stores from applications, allowing them to interact with a unified interface while the gateway handles the complexity of routing to different connectors and data stores.
Solution Approach 2:
The gateway is designed as a universal component that can handle multiple types of data stores through different connectors. Rather than requiring separate integration mechanisms for each data store type, the gateway provides a single unified interface that can route to various data stores (relational databases, NoSQL databases, file systems, cloud services) through appropriate connectors, making the system multi-functional while maintaining a consistent interface.
2Reliability
If existing middleware is used for routing communication between applications and data stores, then basic connectivity is achieved, but scalability and extensibility are limited
Solution Approach 1:
The system segments the middleware functionality into separate, independent connectors, each responsible for a specific data store type. Rather than having a monolithic middleware that tries to handle all data stores, the system uses multiple specialized connectors (e.g., one for relational databases, another for NoSQL, another for file systems). Each connector can be independently developed, deployed, scaled, and extended, improving both scalability and extensibility while maintaining reliable connectivity through specialized implementations.
Solution Approach 2:
The connector registry dynamically registers and manages connectors at runtime, allowing the system to adapt to new data store types without requiring system-wide reconfiguration. Connectors can be dynamically added to the registry, enabling the system to scale and extend its capabilities flexibly. The gateway dynamically selects and uses appropriate connectors based on the data store type, allowing the architecture to evolve as new data store requirements emerge.
3Adaptability or versatility
If multiple connectors are deployed to support various data systems, then data system compatibility is improved, but deployment and management complexity increases
Solution Approach 1:
The gateway acts as a central intermediary that manages all connectors uniformly. Rather than requiring separate deployment and management processes for each connector, the gateway provides a standardized interface for connector registration, configuration, and lifecycle management. The connector registry maintains a centralized list of available connectors and their configurations, simplifying deployment by allowing connectors to be registered and managed through a single unified mechanism rather than individually.
Solution Approach 2:
Connectors are designed to be self-registering components that automatically register themselves with the connector registry upon deployment. Each connector includes metadata about its supported data store types and capabilities, which it automatically publishes to the registry. This self-service approach eliminates the need for manual configuration and registration of each connector, reducing deployment and management complexity while maintaining support for multiple data systems.
Data Source
AI summary
Systems and methods include execution of a first instance of a connector registry service to receive a first registration request from a first instance of a first connector to a first data system, the first registration request comprising a first connector identifier, a first connection type and a first endpoint type, store the first connector identifier, the first connection type and the first endpoint type in a data store, read a plurality of associated connector identifiers, connection types and endpoint types from the data store, the plurality of associated connector identifiers, connection types and endpoint types including the first connector identifier, the first connection type and the first endpoint type, and transmit the plurality of associated connector identifiers, connection types and endpoint types to a first instance of a gateway service.