Webhook-Based Differential Data Structure Synchronization
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Solution Overview
Problem
Checking for updates to structured data, such as event or transactional data, consumes significant processing resources and is time-consuming for user devices, which also struggle to determine which updates are associated with new or existing entries.
Innovation Solution
Implementing a system for remote tracking of updates using webhooks, where an aggregation system receives updates from a data source and generates differential data structures, pushing these updates to user devices efficiently, thereby reducing processing load and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user devices check for updates to structured data, then data synchronization is achieved, but processing resources are consumed and time is lost
Solution Approach 1:
The patent introduces an intermediary server that acts as a mediator between the data source and user devices. The server receives updates from the data source, processes them into differential data structures, and pushes them to user devices via webhooks. This eliminates the need for user devices to directly check for updates, thereby reducing processing resource consumption while maintaining reliable data synchronization.
Solution Approach 2:
The system performs preliminary actions by pre-processing update data into differential data structures before pushing to user devices. The server proactively prepares and transmits only the necessary change information when updates occur, rather than requiring user devices to periodically check for changes, thus saving processing resources and time.
2Reliability
If user devices check for updates to structured data, then data synchronization is achieved, but time is consumed and latency increases
Solution Approach 1:
The intermediary server handles the time-consuming task of update detection and processing centrally. When updates occur at the data source, the server immediately processes them and pushes the differential data structures to user devices via webhooks, eliminating the time delay associated with user devices periodically checking for updates.
Solution Approach 2:
The system establishes continuous notification through webhooks that immediately transmit updates to user devices as soon as changes occur at the data source. This continuous action eliminates the intermittent checking approach, ensuring real-time synchronization without time loss.
3Measurement precision
If user devices determine which updates are associated with new or existing entries, then data processing accuracy is improved, but processing complexity increases
Solution Approach 1:
The server assumes the role of the intermediary that determines whether updates are for new or existing entries by processing the differential data structures centrally. This centralizes the complex determination logic in the server rather than requiring each user device to independently analyze update types, thereby reducing device processing complexity while maintaining accurate update identification.
Data Source
AI summary
In some implementations, an aggregation system may receive, from a user device, a registration message. The aggregation system may receive, from a data source, an initial set of structured data. The aggregation system may receive, from the data source and periodically, updates to the initial set of structured data. The aggregation system may transmit, to the user device and via a webhook activated based on the registration message, an indication of each update. The aggregation system may generate, based on each update, a corresponding differential data structure. The aggregation system may transmit, to the user device, each corresponding differential data structure.