Amazon DynamoDB
SINK

Amazon DynamoDB

Effortlessly load transformed data from GlassFlow into Amazon DynamoDB for scalable, low-latency storage

Integration screenshot

Overview

Amazon DynamoDB Sink Connector

The Amazon DynamoDB Sink Connector allows you to easily load transformed data from GlassFlow into Amazon DynamoDB, a fully managed NoSQL database service.
This connector ensures that your data is efficiently stored and available for real-time applications, offering seamless integration for scalable and low-latency data storage.

Key Features

  • Efficient Data Loading: Seamlessly push transformed data from GlassFlow into DynamoDB tables with minimal latency.
  • Scalable Storage: Leverage DynamoDB’s automatic scaling to handle high-volume data without compromising performance.
  • Real-Time Data Integration: Enable fast, real-time access to data by storing it directly in DynamoDB for low-latency applications.
  • Flexible Data Structure: Store structured and semi-structured data with DynamoDB’s flexible schema design, supporting both key-value and document models.
  • Secure Data Handling: Ensures encrypted data transfer and compliance with security protocols for sensitive data storage.

Use Cases

  • Real-Time Applications: Store and retrieve data quickly for use in real-time applications such as IoT, gaming, or mobile apps.
  • Scalable Web and Mobile Solutions: Use DynamoDB to power scalable and highly responsive backend systems for web and mobile platforms.
  • Data Archiving: Store large amounts of processed data for future retrieval, analysis, or further processing, all within a secure and highly available database.

With the Amazon DynamoDB Sink Connector, GlassFlow provides an efficient way to push transformed data directly into DynamoDB, ensuring you can scale seamlessly while maintaining low-latency data access.

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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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