Showing 5 open source projects for "cloud project"

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  • 1
    ElasticJob

    ElasticJob

    Distributed scheduled job framework

    ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system.
    Downloads: 0 This Week
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  • 2
    Zingg

    Zingg

    Scalable master data management and identity resolution

    Zingg is an open-source entity resolution and master data management platform for finding duplicate, related, or matching records across large datasets. It uses machine learning to learn how records should be compared, reducing the need for brittle hand-written matching rules. The project is designed for data engineering and analytics teams working on customer 360, supplier 360, deduplication, fuzzy matching, data quality, and golden record workflows. Zingg runs on Apache Spark and can scale to large data lake, warehouse, and cloud platform environments. It supports configuration-driven pipelines where users define input data, match fields, training data, models, and output destinations. ...
    Downloads: 0 This Week
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  • 3
    PULSAR

    PULSAR

    Distributed pub-sub messaging system

    Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project. Easy to deploy, lightweight compute process, developer-friendly APIs, no need to run your own stream processing engine. Run in production at Yahoo! scale for over 5 years, with millions of messages per second across millions of topics.
    Downloads: 0 This Week
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  • 4

    MarDRe

    MapReduce-based tool to remove duplicate DNA reads

    ...MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing.
    Downloads: 0 This Week
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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

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  • 5
    Seldon Server

    Seldon Server

    Machine learning platform and recommendation engine on Kubernetes

    ...Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production. Seldon Core is a progression of the goals of the Seldon-Server project but also a more restricted focus to solving the final step in a machine learning project which is serving models in production. Seldon Server is a machine learning platform that helps your data science team deploy models into production. It provides an open-source data science stack that runs within a Kubernetes Cluster. You can use Seldon to deploy machine learning and deep learning models into production on-premise or in the cloud (e.g. ...
    Downloads: 0 This Week
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