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

100 practiced

Compare an append-only event store versus normalized relational event tables for implementing an audit trail that supports frequent writes and reads. Discuss indexing, compaction/archival, queryability for point-in-time reconstruction, and storage costs.

MediumSystem Design

82 practiced

For high-volume time-series telemetry data, describe partitioning strategies you would use: range partitions by time, hash partitions, or a hybrid. Explain retention, compaction, and how you would prune old partitions efficiently.

MediumTechnical

103 practiced

Explain materialized views, their use-cases, and refresh strategies. Provide examples where a materialized view is preferable to a plain view and discuss maintenance costs in OLTP systems.

MediumTechnical

91 practiced

Write a SQL statement to de-duplicate a table customers_raw(customer_email, name, created_at) keeping the earliest created_at per email and deleting duplicates. Use standard SQL and state assumptions about indexes and transactional safety.

MediumSystem Design

101 practiced

You need to shard user data to scale. Describe criteria for choosing a shard key, techniques to avoid hotspots, and strategies for re-sharding with minimal downtime and data movement.

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