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.

MediumTechnical

87 practiced

Design a shard key and partitioning strategy for an orders table that receives millions of records per day. Requirements: support transactional updates, efficient range queries by date, reporting per customer, and avoid shard hotspots. Explain your choice and how you'd handle re-sharding in production.

EasyTechnical

74 practiced

Describe common index types (B-tree, hash, composite, full-text, GiST/GIN) and when each is appropriate. As a Solutions Architect, explain how index choice affects write throughput, storage, and query latency. Give an example trade-off when adding a composite index to accelerate a multi-column WHERE clause.

MediumTechnical

103 practiced

Discuss schema-first (normalized) versus query-driven / denormalized modeling for a microservice that must support ad-hoc queries from downstream analytics teams. As a Solutions Architect, recommend an approach and explain how you would balance developer productivity, query performance, and maintainability.

EasyTechnical

96 practiced

List the top metrics and alerts you would configure to monitor a production database cluster (both OLTP and OLAP examples). For each metric, explain why it matters and suggest reasonable thresholds or alerting strategies for noisy environments.

MediumSystem Design

75 practiced

Design a multi-region transactional database architecture for a global user base of 10M users and peak load of 100k TPS. Requirements: low read latency in each region, single-source-of-truth per user, and ability to handle region failure. Propose technologies, replication topology, conflict-resolution and justify trade-offs between latency and consistency.

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