4 个仓库
Mechanisms for passing references to remote stateful services across distributed task boundaries.
Distinguishing note: Focuses on the serialization and transmission of actor references rather than general data object passing.
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Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f
Ray allows passing actor handles as arguments to remote tasks to enable distributed components to interact with the same stateful service.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Enables efficient remote interaction with shared data structures by transmitting object identifiers across the cluster.
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。
Provides an abstraction layer over distributed data structures so developers interact with them like local JavaScript objects.
Capnweb is a distributed object communication library and Cap'n Proto RPC framework. It enables type-safe remote procedure calls between clients and servers using shared schemas and generated stubs to invoke methods on remote objects as if they were local. The project utilizes an object-capability security model to govern access to remote resources through unforgeable tokens. It provides a bidirectional network layer that multiplexes asynchronous calls and data streams over persistent WebSocket connections and includes a remote resource lifecycle manager that uses reference counting to automa
Implements shared object abstractions that allow developers to interact with distributed data structures as if they were local.