Google Pub/Sub
SOURCE

Google Pub/Sub

Google Pub/Sub is a fully-managed messaging service by Google Cloud. GlassFlow connector to Google Pub/Sub can consume messages directly from your Pub/Sub topic and send it to your pipeline

Integration screenshot

Overview

Google Pub/Sub Source Connector

The Google Pub/Sub Source Connector allows you to seamlessly stream real-time messages from Google Pub/Sub into GlassFlow for processing, transformation, and integration.
By leveraging Google’s scalable messaging service, this connector makes it easy to process event-driven data in real time, enabling dynamic, high-performance workflows.

Key Features

  • Real-Time Message Streaming: Capture and stream messages as they are published to Google Pub/Sub topics.
  • Event-Driven Data Processing: Process incoming messages in real time to trigger automated actions or analytics.
  • Scalable Integration: Handle high-volume streams of messages with minimal latency, ensuring timely data delivery.
  • Customizable Filtering: Filter specific messages or topics for processing based on your data pipeline requirements.
  • Secure and Reliable: Uses secure, encrypted connections to ensure the safe transfer of data.

Use Cases

  • Event-Driven Applications: Integrate with Google Pub/Sub to trigger real-time actions or updates based on message content.
  • Real-Time Data Pipelines: Stream data into GlassFlow for immediate processing, transformation, and analysis.
  • Scalable Messaging: Capture high-volume message data from Google Pub/Sub and integrate it into your data ecosystem without bottlenecks.

With the Google Pub/Sub Source Connector, GlassFlow provides an easy way to process and act on real-time data from your Google Pub/Sub topics, empowering faster, event-driven decision-making.

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Supported by our users

Do not listen to us. Listen to them.

  • GlassFlow team managed to turn my scattered thoughts regarding the data streaming into a Python masterpiece.
    ⁠Anurag Roy@Doorlabs
  • Creating a data pipeline with GlassFlow is incredibly straightforward
    ⁠Swapnil Gupta@Deloitte
  • I am fed up with overcomplicated event-based pipelines. Finally a team that will make my life easier.
    Philippe Brule@aboutphilippe
  • Love the way they team tackles the complexity of building and sharing streaming pipelines.
    Rakesh Kaswan@KaswanRakesh
  • As a Python dev starting with data streaming, you should absolutely give Glassflow a try.
    ⁠Dinesh Marimuthu@Bilthouse
  • Something is cooking here! Super excited to test your solution.
    Joash Xu@joashxu
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