How to Source Data From Amazon DynamoDB to Confluent

Amazon DynamoDB, a serverless NoSQL database known for its high availability and scalability, can be effectively paired with Confluent's data streaming platform to achieve real-time data processing through change data capture (CDC). Confluent enhances the capabilities of Apache Kafka by offering greater elasticity, storage, and throughput, allowing data from DynamoDB to be quickly processed and delivered for diverse applications such as real-time analytics, integration with other systems, disaster recovery, data lake hydration, and multi-cloud strategies. DynamoDB's native options for capturing data changes, DynamoDB Streams and Kinesis Data Streams, come with certain limitations, such as data retention and delivery guarantees, which can be mitigated by integrating with Confluent. The blog post explores three architectural patterns for implementing CDC: using DynamoDB Streams with AWS Lambda, leveraging Kinesis Data Streams with no-code Confluent connectors, and employing a self-managed open-source Kafka connector with Elastic Kubernetes Service (EKS). Each method offers distinct benefits and considerations, such as cost-effectiveness, ease of scaling, and operational complexity, allowing organizations to choose the most suitable approach based on their specific needs and infrastructure.

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