基于Raft协议的Django多源数据同步方法及系统

By introducing a middleware component of the Raft protocol into the Django framework, multi-source data nodes are automatically managed and a Raft cluster is established. This solves the complexity and consistency problems of multi-source data synchronization under the Django framework, and achieves efficient and reliable data synchronization and high system availability.

CN120075247BActive Publication Date: 2026-07-17BEIMI TECHNOLOGY (ZHUHAI) CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIMI TECHNOLOGY (ZHUHAI) CO LTD
Filing Date
2025-02-27
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In the Django framework, multi-source data synchronization suffers from single point of failure, data synchronization delay, difficulty in ensuring data consistency, and high development and maintenance complexity. Existing solutions such as ZooKeeper and Kafka have high deployment costs and network partitioning issues.

Method used

Using the Raft protocol as a middleware component, it automatically discovers and manages multiple data source nodes, assigns node roles according to the rules of the Raft protocol, establishes a Raft cluster, and uses election threads, data synchronization threads, and periodic synchronization threads to ensure data consistency. It also supports dynamic adjustment of running parameters to achieve seamless integration and high availability.

Benefits of technology

It achieves efficient and reliable multi-source data synchronization, reduces deployment complexity, improves data consistency and system flexibility, adapts to node failures and network partitions, reduces synchronization overhead, and improves system high availability and performance.

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Abstract

本申请涉及分布式计算技术领域,公开了一种基于Raft协议的Django多源数据同步方法及系统。该方法通过在Django框架中集成Raft共识算法设计为无侵入式中间件组件,实现了多数据源节点的自动发现与动态管理,并通过选举线程、数据同步线程和周期同步线程协同工作,保障分布式系统的数据一致性和高可用性。所述方法支持动态表结构比对与同步,通过增量同步机制优化数据同步性能,并通过热更新机制动态调整运行参数以适应不同业务场景的需求。本申请显著提升了多源数据同步系统的一致性、灵活性和运行效率,适用于分布式环境下的多源数据库管理场景。
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