Showing 3 open source projects for "tftp-server"

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    Apache Kyuubi

    Apache Kyuubi

    Apache Kyuubi is a distributed and multi-tenant gateway

    ...Kyuubi provides a pure SQL gateway through Thrift JDBC/ODBC interface for end-users to manipulate large-scale data with pre-programmed and extensible Spark SQL engines. This "out-of-the-box" model minimizes the barriers and costs for end-users to use Spark at the client side. At the server-side, Kyuubi server and engines' multi-tenant architecture provides the administrators a way to achieve computing resource isolation, data security, high availability, high client concurrency, etc.
    Downloads: 4 This Week
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    ScalikeJDBC

    ScalikeJDBC

    A tidy SQL-based DB access library for Scala developers

    ...Whether you like it or not, JDBC is a stable standard interface. Since most of RDBMS supports JDBC interface, we can access RDBMS in the same way. We believe that ScalikeJDBC basically works with any other RDBMS (Oracle, SQL Server and so on). If you can access some datastore via JDBC interface, that means you can access them via ScalikeJDBC too. Recently, Amazon Redshift and Facebook Presto support JDBC interface. You can access them via ScalikeJDBC! Of course, you can use c3p0 (or others) instead of commons-dbcp though ConnectionPool implementation for that isn’t provided by default.
    Downloads: 0 This Week
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  • 3
    Apache PredictionIO

    Apache PredictionIO

    Machine learning server for developers and ML engineers

    Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.
    Downloads: 0 This Week
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