Commit Graph Data Management for Low-Latency Collaboration
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Solution Overview
Problem
Existing collaborative data management systems fail to efficiently store and manage data in a manner that supports multiple users with low latency, real-time feedback, and version history, particularly in high-frequency content creation applications, leading to performance bottlenecks and workflow complications.
Innovation Solution
A system that utilizes a commit graph with property sets and change sets to store data, enabling low latency, simultaneous access, and efficient branching and merging, while maintaining a complete change history and supporting rich data models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional file system data management is used for collaborative content creation, then data storage is simple, but latency is high and real-time collaboration is not supported
Solution Approach 1:
The patent segments the data management system into multiple independent components: property sets for data organization, change sets for version control, and commit graphs for history tracking. This segmentation enables parallel processing and reduces access latency while maintaining manageable complexity through clear separation of concerns.
Solution Approach 2:
The patent introduces a temporal dimension to data management by organizing data in commit graphs that track changes over time. This allows the system to provide fast access to historical versions while maintaining current state data, effectively adding a time-based dimension that resolves the conflict between speed and complexity.
2Reliability
If complete change history is maintained for all users, then version control is comprehensive, but data synchronization latency increases
Solution Approach 1:
The patent extracts the change history functionality into a separate commit graph structure that is independent from the main data storage. This allows the system to maintain complete version histories without burdening the primary data access paths, thereby preserving reliability while minimizing synchronization time impact on active collaboration.
Solution Approach 2:
The system creates lightweight copies of data in change sets that capture only the differences from previous versions. This copying mechanism enables comprehensive version control while reducing the amount of data that needs to be synchronized, thus maintaining reliability without significant time loss.
3Adaptability or versatility
If multiple users access and edit data simultaneously, then collaboration capability is enhanced, but data consistency becomes difficult to maintain
Solution Approach 1:
The patent introduces property sets as intermediary structures that mediate between multiple users and the underlying data storage. These property sets provide a standardized interface for data access and modification, enabling multiple users to collaborate simultaneously while maintaining data consistency through structured property definitions and validation rules.
4Loss of information
If detailed version history is stored for every change, then reversion capability is complete, but bandwidth usage increases
Solution Approach 1:
The patent implements change sets that store only the partial information necessary to represent modifications - specifically, the differences between versions rather than complete copies. This partial action approach preserves complete reversion capability while minimizing bandwidth usage by transmitting and storing only the essential change data.
Data Source
AI summary
A method and system provide the ability to manage data. Property sets consisting of property set objects are created. A commit graph stores the property set objects and provides a topology of changes between states of the objects as commit nodes. Change sets represent a change between two commit nodes. Each change set specifies a basic operation that was applied on each state to get to a next state of the property set objects and each change set is reversible.