By using a serverless Glue streaming job to continuously pull your MSK records, transform them as needed, and land them in Parquet (or another columnar) files in S3, you:
1. Optimize storage costs ?your data sits in S3, where you pay pennies per GB-month and can tier it further with lifecycle rules.
2. Get low-latency access ?Redshift Spectrum lets you query S3-backed tables with millisecond planning time, so freshly landed data becomes queryable almost immediately.
3. Minimize ops overhead ?you don't have to stand up or manage any EC2-based brokers, Lambda polling loops, or custom connector infrastructure.
Glue's managed streaming runtime handles checkpointing, autoscaling, and fault tolerance for you.
Once the data lands in S3, you simply define an external schema in Redshift that points at the Glue Data Catalog database where your streaming job writes tables. Analysts can then query the
"live" dataset via Spectrum as if it were inside Redshift, meeting both your performance and cost goals with minimal operational effort.