Mongo DB
SOURCE

Mongo DB

Stream real-time data from MongoDB into GlassFlow for processing, transformation, and integration

Overview

MongoDB Source Connector

The MongoDB Source Connector enables you to stream real-time changes from MongoDB databases directly into GlassFlow for processing, transformation, and integration.
Leveraging MongoDB's Change Streams, this connector captures updates, inserts, and deletes in real time, making it ideal for event-driven applications and dynamic data pipelines.

Key Features

  • Real-Time Data Capture: Stream changes from MongoDB as they happen, capturing inserts, updates, and deletes in real time.
  • Seamless Integration: Easily integrate MongoDB with GlassFlow for efficient data processing and seamless workflows.
  • Low Latency Processing: Ensure fast, near-instantaneous data flow from MongoDB to GlassFlow, enabling rapid decision-making.
  • Flexible Data Handling: Filter or modify incoming data before it enters downstream systems, tailoring it to your specific needs.
  • Secure and Reliable: Transfer data securely with encrypted connections and comply with industry standards for data protection.

Use Cases

  • Real-Time Analytics: Stream MongoDB data into analytics platforms or dashboards for live reporting and insights.
  • Event-Driven Automation: Trigger actions or workflows based on real-time data changes in MongoDB, enabling automated responses.
  • Data Synchronization: Sync MongoDB data across different applications or systems to ensure consistency and accuracy.

With the MongoDB Source Connector, GlassFlow helps you build responsive, real-time data pipelines by seamlessly integrating MongoDB with your data workflows.

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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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