What enables real-time processing of streaming big data in AWS?

Amazon Kinesis Data Streams is designed specifically for real-time processing of streaming big data within the AWS ecosystem. It enables the collection, processing, and analysis of data as it is generated, allowing organizations to respond to new information immediately. Kinesis Data Streams allows users to ingest large volumes of data in real time from various sources, such as IoT devices, logs, or user interactions.

With Kinesis, you can build applications that process and analyze streaming data continually, offering the capabilities to scale seamlessly based on the workload. This service provides mechanisms for buffering, processing data records, and integrating with other AWS services seamlessly.

In contrast, the other options serve different purposes. Amazon S3 is primarily for object storage, offering durability and scalability for large data sets but does not facilitate real-time processing. Amazon Redshift is a data warehousing service optimized for analytics of large datasets but works primarily with data that has been stored rather than streaming data. Similarly, Amazon DynamoDB is a NoSQL database designed for key-value and document data and is not intended specifically for real-time data stream processing. Thus, for real-time big data processing, Amazon Kinesis Data Streams is the most appropriate choice.