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.

HardTechnical

45 practiced

Your monthly database bill spiked unexpectedly after a product launch. Walk through how you would investigate cost drivers across storage, IO, read/write counts, cross-region replication, instance sizing, and backups. What immediate mitigations would you apply and what longer-term controls would you put in place to prevent recurrence?

HardSystem Design

45 practiced

Architect read-write separation for a Postgres cluster serving both OLTP and analytical workloads. Requirements: 10k TPS for writes, complex analytical queries must not impact write tail latency, and eventual consistency for analytics is acceptable. Discuss replica lag, async replicas, query routing, materialized views, logical replication to analytical stores, and SLO maintenance.

HardTechnical

35 practiced

Design how you'd ensure encryption, access controls, audit logging, and data residency for a database storing PII across multiple regions. Discuss key management (KMS), role-based access, audit-log retention and integrity, performance impacts of encryption, and how you'd test and monitor compliance continuously.

HardTechnical

34 practiced

You deploy a new database engine and discover observability gaps: no metrics for compaction, GC, or disk stalls, and slow queries are not correlating with CPU or I/O. How would you instrument the system to capture relevant telemetry, design dashboards and alerts, and validate that the new signals correlate with user-impacting incidents?

HardSystem Design

35 practiced

Design a disaster recovery plan for a critical user-data store with RPO=0 and RTO=15 minutes. Discuss multi-site synchronous replication, quorum requirements, automated failover procedures, validation of data integrity after failover, and regular DR testing including runbooks and rollback steps.

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