Showing 4 open source projects for "throughput"

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    Gatling

    Gatling

    Modern Load Testing as Code

    ...Gatling supports HTTP out of the box as well as WebSocket, Server-Sent Events, and JMS, so you can exercise modern, real-time systems end to end. Rich HTML reports visualize percentiles, response time distributions, errors, and throughput, making bottlenecks and regressions easy to spot. With injection profiles (ramp, constant, spikes) and pass/fail gates, you can automate performance thresholds in CI and promote builds with confidence.
    Downloads: 11 This Week
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  • 2
    Scalatra

    Scalatra

    Tiny Scala high-performance, async web framework

    Scalatra is a lightweight, high-performance micro web framework written in Scala, inspired by the Ruby framework Sinatra. Its goal is to provide a minimal but expressive foundation for building web applications or REST APIs in Scala without the verbosity or steep learning curve of larger frameworks. It supports asynchronous request handling, routing, filters, content negotiation, and easy integration with templating, JSON libraries, and other web middleware. Being unopinionated, it lets...
    Downloads: 0 This Week
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  • 3
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    ...With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster.
    Downloads: 0 This Week
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  • 4
    SnappyData

    SnappyData

    Memory optimized analytics database, based on Apache Spark

    SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over large volumes of data with minimal or no pre-processing of the dataset. ...
    Downloads: 0 This Week
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