Database Design and Architecture Questions

Designing and architecting databases for production and cloud environments with attention to data modeling, schema design, and access pattern optimization. Topics include normalization and denormalization trade offs, schema versus query driven modeling, entity and relationship design for transactional and analytical workloads, indexing and query optimization techniques, partitioning and sharding design decisions, schema evolution and migration strategies, materialized views and caching strategies, selection of storage layers for different data shapes, and practical operational runbooks for provisioning, monitoring, alerting, backups, disaster recovery, and capacity planning. Candidates should justify schema and architecture choices with respect to latency, throughput, development and operational complexity, maintainability, and cost.

HardTechnical

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Compare storage engines like InnoDB, RocksDB, and WiredTiger for OLTP workloads. Discuss how each handles write amplification, compaction, concurrency, crash recovery, and the types of workloads they excel at.

HardTechnical

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You are migrating an on-prem relational database to a cloud managed service. Create a capacity planning model covering vCPU, memory, IOPS, storage, and cost. Explain how you would measure current workload and project cloud sizing and costs.

EasyTechnical

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Compare OLTP and OLAP systems and explain how their different workloads affect data modeling, indexing, storage choices, and schema normalization for a typical e-commerce application.

EasyTechnical

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What is a query execution plan? As a Software Engineer, explain how you would use EXPLAIN or EXPLAIN ANALYZE output to diagnose a slow select that joins three large tables.

HardSystem Design

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You must scale writes to 100k transactions per second for a relational workload. Propose a sharding design, discuss re-sharding mechanics, strategies to avoid hotspots, and how to handle cross-shard transactions or joins.

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