Showing 2 open source projects for "flink"

View related business solutions
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • Build Data Resilience - Take the Assessment Today Icon
    Build Data Resilience - Take the Assessment Today

    Can you recover when it matters most? Take this quick assessment to identify gaps and build greater recovery confidence.

    Is your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
    Take the Assessment
  • 1
    Bytewax

    Bytewax

    Python Stream Processing

    Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. ...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next