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Database Fundamentals and Storage Engines Questions

Core principles and components of data storage and persistence systems. This includes storage engine architectures and how they affect query processing and performance; transactions and isolation including atomicity, consistency, isolation, and durability; concurrency control and isolation levels; indexing strategies and how indexes affect read and write amplification; physical versus logical storage and object, block, and file storage characteristics; caching layers and cache invalidation patterns; replication basics and how replication affects durability and read performance; backup and recovery techniques including snapshots and point in time recovery; trade offs captured by consistency, availability, and partition tolerance reasoning; compression, cost versus performance trade offs, data retention, archival, and compliance concerns. Candidates should be able to reason about durability, persistence guarantees, operational recovery, and storage choices that affect latency, throughput, and cost.

MediumTechnical
47 practiced
Implement a simple in-memory LRU cache in Python supporting O(1) get and put, a maximum capacity, and an optional per-entry TTL (time-to-live). Provide code or clear pseudocode and describe how expiry is handled on access and eviction.
MediumTechnical
72 practiced
You're onboarding a multi-tenant OLTP service that requires per-tenant encryption at rest, variable retention policies, and the ability to restore a single tenant to a point-in-time. Describe storage architecture and encryption key management approaches that satisfy these requirements and estimate cost trade-offs.
MediumTechnical
41 practiced
You're operating a RocksDB-backed OLTP service (LSM). Query and write latencies spike during compaction windows. Describe the debugging steps, key metrics to collect, and immediate mitigations you can apply without changing client behavior. Include long-term changes you might make.
EasyTechnical
75 practiced
Compare row-oriented and column-oriented storage formats. Explain their performance characteristics (IO patterns, compression, CPU usage) and recommend which you'd choose for: a) high-frequency OLTP point reads/writes, and b) analytical large scans and aggregations. Give examples of file formats for each.
MediumSystem Design
48 practiced
Design a backup and recovery strategy for a critical Postgres transactional database with RPO = 1 minute and RTO = 15 minutes. Include base snapshot cadence, WAL archiving/streaming, cross-region considerations, retention policy, and a testing/validation plan for restores.

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