Showing 2 open source projects for "aras-common"

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  • Compliant and Reliable File Transfers Backed by Top Security Certifications Icon
    Compliant and Reliable File Transfers Backed by Top Security Certifications

    Cerberus FTP Server delivers SOC 2 Type II certified security and FIPS 140-2 validated encryption.

    Stop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
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  • Enterprise-grade ITSM, for every business Icon
    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 1
    doobie

    doobie

    Functional JDBC layer for Scala

    doobie is a pure functional JDBC layer for Scala and Cats. It is not an ORM, nor is it a relational algebra; it simply provides a functional way to construct programs (and higher-level libraries) that use JDBC. For common use cases doobie provides a minimal but expressive high-level API. doobie is a Typelevel project. This means we embrace pure, typeful, functional programming, and provide a safe and friendly environment for teaching, learning, and contributing as described in the Scala Code of Conduct. Note that doobie is pre-1.0 software and is still undergoing active development. ...
    Downloads: 0 This Week
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  • 2
    SnappyData

    SnappyData

    Memory optimized analytics database, based on Apache Spark

    ...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. For instance, there is no need to often pre-aggregate/reduce or generate cubes over your large data sets for ad-hoc visual analytics. This is made possible by smartly managing data in memory, dynamically generating code using vectorization optimizations, and maximizing the potential of modern multi-core CPUs. ...
    Downloads: 0 This Week
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