Design a Data Pipeline Service
Last updated: January 19, 2026
Quick Overview
Design a low-latency data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
PlanetScale
January 19, 2026229
12
1,701 solved
Design a low-latency data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
PlanetScale asks this during the Technical Screen 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
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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 optimize costs as the system scales?
- How would you handle schema migrations with zero downtime?
- What would the deployment pipeline look like for this system?
- How do you ensure data consistency across multiple services?
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Requirements
- Functional Requirements:
- Real-time data ingestion: The system must handle millions of incoming data requests per second from various sources.
- Data transformation: Ability to proc...
Capacity Estimation
Assuming an average of 5 million requests per second:
- Data size: Assuming each request carries 1 KB of data, total data per second = 5 million * 1 KB = 5 GB/s.
- Data retention: If we retain...
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