A real-time analytics application must ingest and transform 5 GB of social media data per minute, then load it into a datastore that supports fast queries. Which architecture meets these requirements?

The correct architecture uses Amazon Kinesis Data Streams for high-throughput, real-time data ingestion, capable of handling 5 GB per minute. Amazon Managed Service for Apache Flink provides real-time data transformation, essential for immediate analytics. Amazon DynamoDB is a NoSQL database offering single-digit millisecond performance at any scale, making it ideal for fast queries on transformed data. Incorrect options: EventBridge is for event routing, not high-volume data ingestion. ElastiCache (Memcached) is an in-memory cache, not a primary datastore for persistent, queryable data. SQS is a message queuing service, not designed for streaming 5 GB/minute of raw data. S3 is object storage, not optimized for fast, real-time queries on structured data. SNS is a messaging service for notifications, not data ingestion. EMR is typically used for batch processing, not real-time transformation. RDS is a relational database, which might struggle with the scale and speed requirements for real-time analytics compared to DynamoDB.