Design a Distributed Key-Value Store
Last updated: March 3, 2025
Quick Overview
Build a distributed KV store with consistent hashing, replication, conflict resolution, and tunable consistency levels.
ByteDance
System Design
Software Engineer
ByteDance
March 3, 2025Software Engineer
System Design Round
System Design
Hard
5
12
2,895 solved
Build a distributed KV store with consistent hashing, replication, conflict resolution, and tunable consistency levels.
General distributed systems fundamentals question. Tests deep understanding of storage system internals beyond surface-level API design.
What the Interviewer Expects
- Implement consistent hashing for data partitioning
- Design replication with configurable consistency levels
- Address conflict resolution with vector clocks or CRDTs
- Discuss CAP theorem trade-offs for different use cases
- Design compaction and garbage collection strategies
Key Topics to Cover
Consistent hashing
Replication
Vector clocks
CAP theorem
Compaction
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- When would you choose eventual consistency over strong consistency?
- How do you handle node failures during writes?
- What is your approach to hot key management?
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Practice System Design ProblemsSample Answer
Requirements
Functional Requirements
- Key-Value Storage: Support CRUD operations for key-value pairs.
- Consistent Hashing: Implement consistent hashing for effective data partitioning.
- **Replica...
Capacity Estimation
Assuming ByteDance needs to support 1 billion keys with an average size of 1KB per key-value pair:
- Total Data Size: 1 billion keys * 1 KB = 1 TB of data.
- Replication Factor: With a replic...
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