4 个仓库
Mechanisms for maintaining shared state across distributed environments with tunable consistency models.
Distinct from State Syncing Reactivity: Candidates focus on CLI config, OS environments, or specific JS Map/Set types rather than distributed database state.
Explore 4 awesome GitHub repositories matching data & databases · Distributed State Synchronization. Refine with filters or upvote what's useful.
Naivechain 是一个教育性区块链实现,旨在演示分布式账本的基础知识。它作为一个工作量证明(PoW)区块链运行,节点通过解决计算难题来验证新区块并保护网络安全。 该系统作为使用 WebSocket 的点对点网络运行,用于传播交易并在节点间同步状态。它包括一个用于生成公钥和私钥对的非对称密钥钱包,使用户能够签署交易并管理数字身份。 节点管理和账本数据检索通过 HTTP 区块链接口处理。该项目涵盖了核心分布式系统功能,包括加密哈希链、点对点网络和分布式状态同步。
Provides mechanisms for maintaining a consistent ledger state across distributed nodes.
FluidFramework 是一个实时协作框架和分布式状态同步引擎。它提供了一个协作数据模型库和一个云同步文档系统,旨在通过有序操作在连接的客户端之间复制数据结构,以确保最终一致性。 该框架利用客户端-服务器中继架构来路由和持久化操作,而无需自定义服务端业务逻辑。它通过共享数据容器管理协作会话的生命周期,并实施冲突解决策略(如“最后写入者胜”)以及乐观更新机制,以保持响应迅速的用户体验。 功能领域涵盖分层数据、键值对和实时文本编辑的同步。该系统包括用于独占操作协调的机制、用于用户界面更新的实时状态订阅,以及用于在企业平台上存储应用数据的集成云文档管理。 该项目包括一个用于原型设计协作功能而无需云部署的本地服务模拟。
Distributes and synchronizes application state across multiple clients using consistent distributed models.
Jazz is a local-first relational database and synchronization framework designed for offline-capable applications. It functions as a reactive state management system that treats database records as the primary source of truth, automatically updating user interfaces in real time as underlying data changes. The project distinguishes itself through a collaborative data synchronization model that utilizes row-level versioning to track branching edit histories. It implements a security engine based on identity-claim row security, which enforces granular permissions on individual records, and suppo
Maintains a reactive shared state between distributed environments using tunable consistency for global transactions.
The reverse-linear-sync-engine is a data synchronization framework designed to manage distributed application state. It provides a system for tracking local data mutations, resolving discrepancies between multiple sources, and maintaining consistency across connected clients through a centralized transaction-based model. The engine distinguishes itself by integrating reactive state observation with a transaction history stack. This combination allows the framework to automatically refresh interface components when data changes while simultaneously enabling precise undo and redo functionality.
Maintains consistent state across distributed clients through transaction-based synchronization.