You have an RDS instance. How would you capture all changes happening in the RDS and maintain an ACID‑compliant table in Redshift, using a virtual fast layer in S3, and then produce reporting‑level data in Redshift?

Use AWS Database Migration Service (DMS) or native binlog replication to stream changes from RDS to an Amazon Kinesis Data Stream. From Kinesis, write the raw change events to an S3 bucket in a partitioned, columnar format (Parquet). This S3 layer acts as a fast, immutable store that can be queried by Redshift Spectrum for near‑real‑time analytics. To maintain an ACID‑compliant table in Redshift, schedule a nightly or hourly COPY from the S3 bucket into a Redshift staging table, then merge the staged data into the main fact table using a UPSERT pattern (INSERT … ON CONFLICT UPDATE). Redshift’s transactional engine guarantees ACID properties. Finally, create materialized views or aggregated tables in Redshift for reporting. This architecture decouples ingestion from analytics, provides durability via S3, and leverages Redshift’s performance for reporting.