Database Selection and Trade Offs Questions

How to evaluate and choose data storage systems and architectures based on workload characteristics and business constraints. Coverage includes differences between relational and nonrelational families such as document stores, key value stores, wide column stores, graph databases, time series databases, and search engines; mapping query patterns and latency requirements to storage options; trade offs between strong consistency and eventual consistency and their impact on availability and complexity; partition key design, replication strategies, and high availability considerations; operational concerns including backups, monitoring, vendor and cost trade offs, migration or hybrid strategies, and when to adopt polyglot persistence. Senior level discussion includes selecting specific managed services and reasoning about expected load patterns, failure modes, and operational burden.

HardSystem Design

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You're designing high-availability for an online checkout service: 99.99% uptime target, global users. Describe replication topology, leader election strategy, and how you'd handle failover with minimal downtime. Include considerations for split-brain, data loss, and client retries.

MediumTechnical

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Describe how to design partition keys for time-series data where queries are mostly: "get metrics for device X over last hour" and occasional cross-device aggregations by region. Propose partition key and clustering strategy to optimize for both access patterns and explain trade-offs.

MediumTechnical

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A company wants to minimize cloud costs for infrequently accessed historical data while keeping it queryable for auditing. Propose a storage and lifecycle strategy across hot, warm, and cold tiers (e.g., primary DB, object storage, archive). Include migration triggers, query routing, and cost-vs-latency trade-offs.

EasyTechnical

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Explain the CAP theorem and how it applies to distributed databases. For each pair (Consistency, Availability, Partition tolerance), provide a short example of a database or configuration that prioritizes that trade-off and the operational consequences for application developers.

MediumTechnical

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Explain how index selection and query planning differ between OLTP and OLAP workloads. Give an example where a design optimized for OLTP (many small transactional writes) performs poorly for analytical aggregations, and how you would change the storage or indexing to support both.

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