A company needs a near-real-time pipeline for high-volume ecommerce clickstream data: ingest, process, and visualize. The solution must support SQL-based processing and Jupyter notebooks for interactive work. Which architecture satisfies these needs?

The correct architecture uses Amazon MSK for high-volume, near-real-time ingestion of clickstream data. Amazon Managed Service for Apache Flink is ideal for processing streaming data with SQL, directly addressing the requirement for SQL-based processing. Flink also supports interactive querying, which can be integrated with Jupyter notebooks. Flink's built-in dashboards provide real-time visualization capabilities. Incorrect options: Kinesis Data Firehose with Lambda is less suitable for complex SQL-based stream processing and interactive analysis. Kinesis Data Streams with Firehose and Athena introduces unnecessary complexity with Firehose for transformation and Athena for batch-oriented SQL processing, not true stream processing. MSK with AWS Glue (PySpark) is good for processing but doesn't inherently offer the same level of real-time SQL processing and interactive notebook integration as Flink for streaming data.