Showing 3 open source projects for "data processing"

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  • 1
    CloudI: A Cloud at the lowest level
    CloudI is an open-source private cloud computing framework for efficient, secure, and internal data processing. CloudI provides scaling for previously unscalable source code with efficient fault-tolerant execution of ATS, C/C++, Erlang/Elixir, Go, Haskell, Java, JavaScript/node.js, OCaml, Perl, PHP, Python, Ruby, or Rust services. The bare essentials for efficient fault-tolerant processing on a cloud!
    Downloads: 7 This Week
    Last Update:
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  • 2

    dispy

    Distributed and Parallel Computing with/for Python.

    dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.
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    Downloads: 13 This Week
    Last Update:
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  • 3
    StreamMine is a distributed event processing (streaming) infrastructure. You can create low-latency, fault-tolerant stream processing functionality with any stream-oriented operators that can be implemented in Python.
    Downloads: 0 This Week
    Last Update:
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