Showing 6 open source projects for "dataflow"

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    Build Securely on AWS with Proven Frameworks

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    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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  • 1
    Apache Beam

    Apache Beam

    Unified programming model for Batch and Streaming

    ...These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers.
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  • 2
    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. Scale out for throughput and...
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  • 3
    Apache Flink

    Apache Flink

    Stream processing framework with powerful stream

    Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level APIs—DataStream and Table/SQL—to express transformations, joins, and stateful patterns, while specialized libraries support CEP, machine learning workflows, and connectors. ...
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  • 4
    Python Taint

    Python Taint

    Static Analysis Tool for Detecting Security Vulnerabilities in Python

    Static analysis of Python web applications based on theoretical foundations (Control flow graphs, fixed point, dataflow analysis) Detect command injection, SSRF, SQL injection, XSS, directory traveral etc. A lot of customization is possible. For functions from builtins or libraries, e.g. url_for or os.path.join, use the -m option to specify whether or not they return tainted values given tainted inputs, by default this file is used.
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    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

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  • 5
    The Squidy Interaction Library eases the design of "post-WIMP" user interfaces by unifying various device drivers, frameworks and tracking toolkits in a common library and provides a central and easy-to-use visual design environment. www.squidy-lib.de
    Downloads: 0 This Week
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  • 6
    sdf4j is a Java framework to manipulate Static Dataflow graphs (SDF).
    Downloads: 0 This Week
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