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AWS Lambda is designed to automatically trigger functions in response to events, and it integrates seamlessly with DynamoDB Streams. When data modifications such as inserts, updates, or deletes occur in a DynamoDB table, those changes can be captured and stored in a stream. AWS Lambda can then be configured to listen to these streams, allowing it to process the changes in real-time, run custom logic, or even perform tasks such as sending notifications or updating other systems.

The ability of AWS Lambda to handle these event-driven processes makes it an ideal solution for real-time data processing scenarios, thereby enhancing the responsiveness of applications relying on data stored in DynamoDB. Other services like AWS Step Functions, AWS Glue, and AWS Batch serve different purposes. While Step Functions orchestrate workflows and Glue is used primarily for ETL (Extract, Transform, Load) jobs, AWS Batch is focused on batch processing and does not offer the same immediate event-driven integration as Lambda does with DynamoDB Streams.