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.

EasyTechnical

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Compare ACID and BASE consistency models. For each model, describe the guarantees, typical database technologies that implement them, and the kinds of applications that benefit from each. As a Solutions Architect, how would you recommend a consistency model for a shopping cart service vs a global user-profile directory?

EasyTechnical

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Describe the differences between a materialized view, an in-memory cache (e.g., Redis), and a normal index. For each, explain how freshness/staleness is handled, when you'd use each in a production architecture, and operational concerns like refresh cost and invalidation.

EasyTechnical

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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.

MediumTechnical

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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.

MediumTechnical

0 practiced

A query joining two billion-row tables is running slowly. As a Solutions Architect, outline a step-by-step plan to diagnose and optimize the query. Include explain plan analysis, index changes, partition pruning, rewriting the query, and fallback strategies such as pre-aggregation or materialized intermediate tables.

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