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

40 practiced

Compare failure modes and backup/restore strategies for managed NoSQL (DynamoDB), managed SQL (Cloud SQL), and object-store-backed data lakes (S3 + Glue). Define RPO/RTO planning, backup cadence, cross-region replication, and describe how you would test restores for each system.

HardSystem Design

62 practiced

Design a real-time clickstream analytics pipeline that supports near-real-time dashboards (<60s latency) and complex historical ad-hoc queries. Include ingestion (Kafka), stream processing (Flink/Spark Streaming), storage tiers (hot DB for recent data, cold data lake), and the query layer. Discuss trade-offs for which storage to use for hot vs cold and indexing strategies.

MediumTechnical

56 practiced

Describe B-tree, LSM-tree, and inverted index structures. For each index type list the workloads they optimize (point lookup, range scan, high-write throughput, full-text search) and give one example database that uses it.

MediumTechnical

40 practiced

Design monitoring, observability, and alerting for a production feature store used for online model serving. Include key SLIs/SLOs, metrics to track (latency, freshness, error rates), dashboards, alert thresholds, and an incident runbook for degraded performance or data drift.

HardSystem Design

38 practiced

You need to migrate a high-throughput OLTP PostgreSQL database to a horizontally scalable NoSQL store (Cassandra/DynamoDB) with minimal downtime. Provide a step-by-step migration plan covering schema translation, data backfill strategy, incremental sync (CDC), dual-write or rewrite strategies, cutover approach, validation, and rollback planning.

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