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.

MediumSystem Design

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Design a low-latency product catalog service that supports frequent updates (prices, inventory) and millions of read requests per minute. Choose between in-memory caching, materialized views, and denormalized read stores. Provide a design that balances update latency, read freshness, cache invalidation complexity, and operational cost.

HardTechnical

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Design a backup and point-in-time recovery strategy for a distributed NoSQL database ingesting 1M writes/sec. Propose how to create incremental snapshots, archive write-ahead logs to object storage, manage retention without excessive cost, and how to perform restores to a specific timestamp.

MediumTechnical

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Explain practical trade-offs between eventual consistency and strong consistency for a distributed application. Use examples (e.g., social feed vs. financial ledger) to illustrate effects on UX, conflict resolution strategies, and how application-level idempotency or compensating actions can mitigate eventual consistency limitations.

HardTechnical

0 practiced

Technical (SQL/procedural pseudocode): Design an online backfill algorithm as a stored procedure or worker pseudocode to populate a new non-null column across 100M+ rows in batches without locking the full table for more than one second. Explain batching, throttling, idempotency, and failure recovery.

MediumTechnical

0 practiced

Design TTL and compaction policies for a key-value store used for web sessions where inactive session records should expire after 30 days. Include strategy for tombstones, compaction frequency, handling long-running queries, and minimizing storage cost while preventing hot partitions.

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