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2 रिपॉजिटरी

Awesome GitHub RepositoriesStream Processing Integrations

Connecting WebAssembly-hosted functions as handlers in data stream processing pipelines for automatic message processing.

Distinguishing note: No candidate in the shortlist covers stream processing integration with WebAssembly; this is a specific integration pattern.

Explore 2 awesome GitHub repositories matching networking & communication · Stream Processing Integrations. Refine with filters or upvote what's useful.

Awesome Stream Processing Integrations GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • wasmedge/wasmedgeWasmEdge का अवतार

    WasmEdge/WasmEdge

    10,665GitHub पर देखें↗

    WasmEdge is an extensible WebAssembly runtime that executes WebAssembly bytecode in a secure sandbox for cloud, edge, and embedded applications. It functions as a multi-language compiler, compiling applications written in Rust, JavaScript, Go, and Python into WebAssembly bytecode for sandboxed execution, and as a server-side JavaScript runtime that runs JavaScript programs with ES6 modules, NPM packages, and Node.js-compatible APIs. The runtime also serves as an AI inference runtime, executing AI models from JavaScript using WASI-NN plug-ins for inference tasks on personal devices and edge har

    Connects WebAssembly-hosted inference functions as handlers in YoMo data streams for automatic image frame processing.

    C++artificial-intelligencecloudcloud-native
    GitHub पर देखें↗10,665
  • hazelcast/hazelcasthazelcast का अवतार

    hazelcast/hazelcast

    6,570GitHub पर देखें↗

    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

    Provides fault-tolerant stream processing pipelines that ingest and transform unbounded event data from external sources.

    Javabig-datacachingdata-in-motion
    GitHub पर देखें↗6,570
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