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mosaicml/streaming

0
View on GitHub↗
1,521 stars·199 forks·Python·Apache-2.0·10 viewsstreaming.docs.mosaicml.com↗

Streaming

A Data Streaming Library for Efficient Neural Network Training

Features

  • Stream Processing - Streams large datasets for distributed model training.
  • Computation and Optimization - Data streaming library for efficient neural network training.

Star history

Star history chart for mosaicml/streamingStar history chart for mosaicml/streaming

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Open-source alternatives to Streaming

Similar open-source projects, ranked by how many features they share with Streaming.
  • airtai/faststreamairtai avatar

    airtai/faststream

    5,234View on GitHub↗

    FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int

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    View on GitHub↗5,234
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    aklivity/zilla

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    🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka® via declaratively defined, stateless APIs.

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  • apache/beamapache avatar

    apache/beam

    8,612View on GitHub↗

    Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded batch data and unbounded real-time streams. It provides a system for building scalable, data-parallel workflows that operate across compute clusters using a single programming model. The framework utilizes a cross-runner pipeline abstraction that decouples the data processing logic from the underlying execution backend, allowing the same pipeline to run on different distributed compute engines. It supports multi-language pipeline development by translating high-level code fro

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    View on GitHub↗8,612
  • adapter-hub/adaptersadapter-hub avatar

    adapter-hub/adapters

    2,815View on GitHub↗

    A Unified Library for Parameter-Efficient and Modular Transfer Learning

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See all 30 alternatives to Streaming→

Frequently asked questions

What does mosaicml/streaming do?

A Data Streaming Library for Efficient Neural Network Training

What are the main features of mosaicml/streaming?

The main features of mosaicml/streaming are: Stream Processing, Computation and Optimization.

What are some open-source alternatives to mosaicml/streaming?

Open-source alternatives to mosaicml/streaming include: airtai/faststream — FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified… aklivity/zilla — 🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka®… apache/beam — Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded… apache/flink — Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite… apache/kafka — Kafka is a distributed event streaming platform designed for capturing, storing, and processing real-time data streams… adapter-hub/adapters — A Unified Library for Parameter-Efficient and Modular Transfer Learning.