Relational Database Fundamentals and Design Questions

Core concepts of relational databases and schema design including tables, relationships such as one to one one to many and many to many, primary keys and foreign keys, data integrity constraints, and the properties of atomicity consistency isolation and durability and why they matter. Understand differences between relational systems using structured query language and nonrelational databases, indexing strategies, normalization and denormalization trade offs, simple query optimization techniques, and when to choose a normalized relational design versus a document or key value store. Candidates should be able to perform basic entity identification, produce simple schema diagrams, explain persistence and durability considerations, and reason about basic performance and scaling trade offs.

HardTechnical

27 practiced

Compare a normalized relational design for an orders system versus storing orders as documents in a document database. Discuss criteria and measurable benchmarks you would collect (latency, throughput, storage size, flexibility, indexability, complexity of queries, transactional needs) to make a data-store decision, and propose an evaluation plan.

MediumTechnical

28 practiced

Compare master-slave (primary-replica) replication and multi-master replication. For each approach, discuss use cases, benefits (read scaling, failover), limitations (write conflicts, consistency), and approaches to conflict resolution and monitoring.

MediumTechnical

27 practiced

Compare ACID guarantees with BASE/eventual consistency models used in some distributed or NoSQL systems. Discuss trade-offs in terms of latency, availability, and developer complexity. Provide examples of applications that can tolerate eventual consistency and techniques to manage the complexity.

HardTechnical

20 practiced

Discuss two-phase commit (2PC) for distributed transactions: how it works, why it's used, and its limitations (blocking coordinator, latency). Present alternatives such as the Saga pattern for long-running distributed workflows and provide a concrete example of implementing a saga with compensation actions.

MediumTechnical

39 practiced

You store millions of event rows with columns: (event_id, user_id, event_type, created_at). Typical queries filter by event_type and created_at range, sometimes by user_id. Propose concrete indexing strategies (single-column, composite, partial, clustering) and explain how each supports query patterns and affects write throughput.

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