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GlassFlow Overview

GlassFlow is a tool to build Event-Driven data pipelines in Python. Users do not need Kafka or Flink and can run end to end data pipelines fully in Python. GlassFlow runs completly serverless without need to configure any clusters or handle complicated infrastructure. Start with our in-built message broker, Google Pub/Sub, Kinesis or our webhook to build your pipeline within 15 minutes.

Getting Started

Vist https://glassflow.dev to learn more or sign up for a free GlassFlow account here

To start running locally, follow the quickstart guide using Jupyter Notebook

To explore more examples, visit the glassflow-examples repository.

Feel free to explore, contribute, and join our slack community! 🚀

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Repositories

Showing 7 of 7 repositories
  • glassflow-examples Public

    Tutorials, templates for running glassflow pipelines

    glassflow/glassflow-examples’s past year of commit activity
    Jupyter Notebook 26 2 0 1 Updated Nov 8, 2024
  • glassflow-python-sdk Public

    GlassFlow Python SDK to publish and consume data to your pipelines at Glassflow.dev

    glassflow/glassflow-python-sdk’s past year of commit activity
    Python 8 MIT 0 1 0 Updated Nov 8, 2024
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    GlassFlow CLI to create and manage real-time data pipelines

    glassflow/cli’s past year of commit activity
    Shell 6 0 0 0 Updated Nov 6, 2024
  • .github Public
    glassflow/.github’s past year of commit activity
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    The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.

    glassflow/airbyte’s past year of commit activity
    Python 0 4,187 0 0 Updated Sep 11, 2024
  • example-real-time-ai-alerts Public

    Real-Time Alerts with AI, NATs and Streamlit

    glassflow/example-real-time-ai-alerts’s past year of commit activity
    Python 9 MIT 1 0 0 Updated Feb 18, 2024

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