Build a real-time Search Pipeline
Last updated: September 1, 2025
Quick Overview
Design a real-time search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Compass
September 1, 202524
7
1,551 solved
Design a real-time search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Compass asks this during the System Design Round to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
What the Interviewer Expects
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
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
- How would you implement rate limiting to protect the system?
- What happens if one of your database nodes goes down?
- How would you handle schema migrations with zero downtime?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
- Functional Requirements:
- Users must be able to perform full-text searches on real estate listings in real-time.
- Search results should be ranked based on relevance, location, price, and u...
Capacity Estimation
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Estimating QPS:
- Assume Compass has approximately 1 million active users.
- If 1% of users search at peak times, that results in 10,000 searches per second.
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Storage Requirements: -...
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