Which solution will meet these requirements with the MOST operational efficiency?
Use Amazon Kinesis Data Streams to ingest data. Use AWS Lambda to analyze the data in real time.
Use AWS Glue to ingest data. Use Amazon Kinesis Data Analytics to analyze the data in real time.
Use Amazon Kinesis Data Firehose to ingest data. Use Amazon Kinesis Data Analytics to analyze the data in real time.
Use Amazon API Gateway to ingest data. Use AWS Lambda to analyze the data in real time.
Explanations:
While using Amazon Kinesis Data Streams and AWS Lambda can enable real-time analysis, it requires additional components to store the data in the data lake (S3). This adds operational complexity.
AWS Glue is primarily used for ETL (extract, transform, load) processes and is not designed for real-time ingestion. Kinesis Data Analytics is suitable for real-time analytics but requires a real-time ingestion solution.
Amazon Kinesis Data Firehose can efficiently ingest data and automatically load it into Amazon S3, allowing for real-time analysis with Kinesis Data Analytics. This solution is designed for operational efficiency in handling streaming data.
Amazon API Gateway is typically used for creating APIs and would not be the most efficient method for ingesting data in real-time compared to Kinesis services. Using Lambda for analysis adds complexity and does not directly facilitate streaming data ingestion.
I compute that the answer is:
Use Amazon Kinesis Data Firehose to ingest data. Use Amazon Kinesis Data Analytics to analyze the data in real time.