Over the years, Amazon DynamoDB has grown into a feature-rich NoSQL database that has deep integrations with various services such as Amazon S3 and AWS Lambda. As businesses increasingly depend on data for decision-making, it is common to use data residing in DynamoDB to contextualize or even drive events at a granular level (as opposed to bulk or batch). By leveraging DynamoDB alongside Confluent’s data streaming platform businesses are able to build event-driven architectures for real-time insights and decision-making.
In a previous blog post we discussed three different ways to capture and transfer data changes from Amazon DynamoDB to Confluent’s data streaming platform. While each approach has its merits, they come with different degrees of complexity. The options include writing and maintaining code with AWS Lambda for data transfer, using the Kinesis Data Streams connector which introduces several intermediate steps, or deploying the open source DynamoDB source connector, which involves self-managing infrastructure and the risk of …