Design a high-throughput Data Pipeline System
Last updated: May 14, 2026
Quick Overview
Design a high-throughput data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Grubhub
May 14, 202614
9
2,851 solved
Design a high-throughput data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at Grubhub. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Grubhub values engineers who can think about scalability from day one.
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 handle a 10x increase in traffic overnight?
- How would you handle a region-wide outage?
- What would the deployment pipeline look like for this system?
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Requirements
Functional Requirements:
- Real-time Data Ingestion: The system must be able to ingest data from multiple sources such as restaurant orders, user interactions, and payment transactions in rea...
Capacity Estimation
To estimate capacity, we need to understand the expected traffic:
- User Base: Assume Grubhub has 10 million active users.
- Orders: If each user places an average of 2 orders per week, that r...
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