**Schema flexibility**: Document (MongoDB), key-value (Redis), wide-column (Cassandra), graph (Neo4j). **Scaling**: Horizontal sharding; eventual consistency. **Why NoSQL**: High write throughput; flexible schema; access-pattern optimization. **Trade-offs**: No ACID across...
This hard-level SQL question appears frequently in data engineering interviews at companies like Nagarro. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, optimization, sql) will help you answer variations of this question confidently.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
Schema flexibility: Document (MongoDB), key-value (Redis), wide-column (Cassandra), graph (Neo4j). Scaling: Horizontal sharding; eventual consistency. Why NoSQL: High write throughput; flexible schema; access-pattern optimization. Trade-offs: No ACID across documents; limited joins; operational complexity. When to use: Session store (Redis); events (Cassandra); recommendations (Neo4j). Cost: Lower ops for schema-less; higher dev cost for modeling.
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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.