Database Architecture and Partitioning Questions

Design database architecture and partitioning strategies appropriate to workload and access patterns. Evaluate database types including relational and various NoSQL models, schema design and indexing strategies, and when to use a monolithic database versus sharding. Cover sharding approaches such as range based, hash based, consistent hashing, and directory based sharding, as well as replica topologies, read replicas, replication lag, and handling cross shard queries. Address operational concerns at scale: resharding, mitigating hot partitions, balancing data distribution, transactional and consistency guarantees, and the trade offs between availability, consistency, and partition tolerance. Include monitoring, migration strategies, and impact on application logic and joins.

EasyTechnical

66 practiced

Explain differences between primary (clustered) and secondary (non-clustered) indexes. Describe how clustered vs non-clustered indexes affect write performance, storage usage, and how they interact with partitioned tables. When would you recommend a bitmap index or inverted index instead of B-tree?

HardTechnical

66 practiced

Compare global secondary indexes in DynamoDB (GSI) and global indexes in Cassandra (global-index approaches). Describe how each system maintains the index, consistency guarantees, write amplification, and limitations when used across shards/partitions for strongly consistent queries.

EasyTechnical

60 practiced

Given this events table schema:

events(event_id PK, user_id, occurred_at TIMESTAMP, event_type, properties JSONB)

Application patterns: frequent recent-time scans (last 7-30 days), occasional backfill scans for months, and low-latency per-user point queries. Propose a partitioning scheme (partition key(s), partitioning granularity, and indexing) that balances both analytic scans and per-user lookups. Explain reasoning and potential weaknesses.

MediumTechnical

51 practiced

You're migrating from a single large Postgres instance to partitioned RDS instances with monthly partitions and read replicas. Outline a migration plan that minimizes application downtime: discovery, schema changes, data backfill strategy, dual-write approaches, cutover, and rollback steps. Include verification checkpoints and how to measure success.

HardTechnical

49 practiced

Design a zero-downtime resharding protocol for a live cluster with 100TB of data and continuous writes. Describe routing changes, write-forwarding vs dual-write options, live data copying strategies, cutover coordination, detection and reconciliation of missed writes, and rollback procedures. Emphasize minimizing user-visible errors and data loss.

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