Showing 4 open source projects for "python software"

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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • 1
    SageMaker Spark Container

    SageMaker Spark Container

    Docker image used to run data processing workloads

    Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data...
    Downloads: 0 This Week
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  • 2
    Wally

    Wally

    Distributed Stream Processing

    Wally is a fast-stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency...
    Downloads: 1 This Week
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  • 3
    Sed.py is a python module to provide a easy way to do text stream processing. Just like the name of module, it likes to do the work that sed can do. But not in sed's way, it's in Python's way. To use this module, the knowledge of regexp is necessary.
    Downloads: 0 This Week
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  • 4
    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
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  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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