**Redshift**: AWS-native, tightly coupled storage/compute, cluster-based; Spectrum for S3 queries; Concurrency Scaling for read bursts. **Snowflake**: Cloud-agnostic, decoupled storage/compute, per-second billing; zero-copy clone, Time Travel, Data Sharing. **Why Redshift**:...
This easy-level SQL question appears frequently in data engineering interviews at companies like S&P Global. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (etl, snowflake) will help you answer variations of this question confidently.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Redshift: AWS-native, tightly coupled storage/compute, cluster-based; Spectrum for S3 queries; Concurrency Scaling for read bursts. Snowflake: Cloud-agnostic, decoupled storage/compute, per-second billing; zero-copy clone, Time Travel, Data Sharing. Why Redshift: Lower TCO for 24/7 steady workloads; deep AWS integration (Glue, Lambda); reserved instances cut cost 40%. Why Snowflake: Variable/spiky workloads; multi-cloud; DevProd parity via clones; sharing for data marketplace. Trade-offs: Redshift requires capacity planning; Snowflake auto-suspend can add cold-start latency. In practice: Redshift for batch ETL and scheduled reports; Snowflake for ad-hoc, multi-tenant, and bursty dashboards.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.