Database Scalability and High Availability Questions

Architectural approaches and operational practices for scaling and maintaining database availability. Topics include vertical versus horizontal scaling trade offs; replication topologies, leader and follower roles, read replicas and replica lag; read write splitting and connection pooling; sharding and partitioning strategies including range based, hash based, and consistent hashing approaches; handling hot partitions and data skew; federation and multi database federation patterns; cache layers and cache invalidation; rebalancing and resharding strategies; distributed concurrency control and transactional guarantees across shards; multi region deployment strategies, cross region failover and disaster recovery; monitoring, capacity planning, automation for failover and backups, and cost optimization at scale. Candidates should be able to pick scaling approaches based on read and write patterns and explain operational complexity and trade offs introduced by distributed data.

HardTechnical

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How would you support cross-shard joins and aggregations for analytics without degrading OLTP performance? Propose approaches such as scatter-gather, pre-aggregation, materialized views, streaming ETL to an analytical store, and secondary indexing. Discuss cost, latency, and operational implications.

HardSystem Design

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Design a multi-master replication system across three regions allowing writes in any region that must deterministically resolve conflicting writes and converge. Include conflict-resolution policies (last-write-wins, CRDTs, application-level merge), metadata required (vector clocks), and operational considerations for partitions and eventual convergence.

MediumTechnical

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Design a data retention and TTL strategy for a multi-tenant analytics database that balances storage cost and query performance. Include tenant isolation considerations, rolling off cold data to cheaper storage, regulatory constraints, and how to implement tiered queries that transparently access cold data.

MediumSystem Design

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Describe a safe plan for rebalancing data when adding capacity to a sharded relational database with live traffic. Cover chunk selection, throttling, routing updates during migration, consistency verification, and rollback strategies in case of failures mid-reshard.

EasyTechnical

0 practiced

Explain the purpose of leader election in distributed databases. Describe common algorithms/systems used (Raft, Paxos, ZooKeeper/etcd), how leader election impacts availability, and what architects must consider during network partitions and leader churn.

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