Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Ingestion**: Kinesis (streaming), DMS (DB migration/CDC), Transfer Family (SFTP), API Gateway + Lambda (REST), EventBridge (events). **Processing**: Glue (managed Spark, ETL), EMR (complex Spark, ML), Lambda (lightweight). **Storage**: S3. **Analytics**: Athena (ad-hoc SQL),...
Ingestion: Kinesis (streaming), DMS (DB migration/CDC), Transfer Family (SFTP), API Gateway + Lambda (REST), EventBridge (events). Processing: Glue (managed Spark, ETL), EMR (complex Spark, ML), Lambda (lightweight). Storage: S3. Analytics: Athena (ad-hoc SQL), Redshift (warehouse). Orchestration: Step Functions, EventBridge. Decision: By latency (real-time vs batch) and volume. Real-time: Kinesis→Lambda→S3. Batch: Glue/EMR from S3. Typical stack: S3 lake, Glue ETL, Athena exploration. Choose Glue for standard batch; EMR for custom Spark/ML.
Pro-Move: 'Our stack: Kinesis for events, Glue for nightly facts, Athena for ad-hoc—documented in our architecture runbook with decision criteria.' Red Flag: Listing services without explaining when to use which—no architectural reasoning.
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