Design product catalog service
System Design: Product Catalog Service for an E-commerce Platform
Context
Design a product catalog service for a large consumer e-commerce platform. This platform manages millions of Stock Keeping Units (SKUs) and features a hierarchical category tree (e.g., Grocery > Produce > Berries). The system is characterized by being read-heavy, supporting frequent merchant updates, and handling bulk imports. It serves as the backbone for critical user-facing features such as product detail pages, category browsing, and search functionalities.
Requirements
Functional Requirements
- APIs:
- CRUD operations for products, categories, and variants/SKUs.
- Full-text search capabilities, including filtering, sorting, pagination, and faceting.
- Asynchronous bulk import functionality, with support for job tracking and idempotency.
Data Model Requirements
- Source of Truth: A relational schema (e.g., PostgreSQL or MySQL) must serve as the primary source of truth.
- Category Hierarchy: The category hierarchy should be modeled using a self-join within the relational database.
- Product Relationships: Support for many-to-many product-category mappings, product variants, attributes, media, and brands.
Non-Functional Requirements
- Scalability: The system must be scalable to handle high read Queries Per Second (QPS) and accommodate periodic write spikes (e.g., during bulk imports or price updates).
- Caching: Implement a comprehensive caching strategy, including object caching, edge caching, and search engine caching, along with robust invalidation mechanisms.
- Consistency: Ensure consistency across the relational database, caches, and search index. Specifically, implement "read-your-writes" consistency for administrative users.
Deliverables
- Define high-level API endpoints for CRUD, search, and bulk import operations, including example request and response structures.
- Propose a relational database schema, explicitly demonstrating the self-join for category hierarchies.
- Discuss strategies for achieving scalability, managing caching, and ensuring consistency.
AI interview prep
Core dilemma
Balancing eventual consistency across multiple data stores (relational DB, cache, search index) with high read throughput and complex search requirements, while adhering to a relational source of truth and specific consistency guarantees like 'read-your-writes' for admins. The challenge lies in efficiently propagating updates and invalidating caches/indexes without sacrificing performance or data integrity.
3 tradeoffs and 2 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Design product catalog service
System Design: Product Catalog Service for an E-commerce Platform
Context
Design a product catalog service for a large consumer e-commerce platform. This platform manages millions of Stock Keeping Units (SKUs) and features a hierarchical category tree (e.g., Grocery > Produce > Berries). The system is characterized by being read-heavy, supporting frequent merchant updates, and handling bulk imports. It serves as the backbone for critical user-facing features such as product detail pages, category browsing, and search functionalities.
Requirements
Functional Requirements
- APIs:
- CRUD operations for products, categories, and variants/SKUs.
- Full-text search capabilities, including filtering, sorting, pagination, and faceting.
- Asynchronous bulk import functionality, with support for job tracking and idempotency.
Data Model Requirements
- Source of Truth: A relational schema (e.g., PostgreSQL or MySQL) must serve as the primary source of truth.
- Category Hierarchy: The category hierarchy should be modeled using a self-join within the relational database.
- Product Relationships: Support for many-to-many product-category mappings, product variants, attributes, media, and brands.
Non-Functional Requirements
- Scalability: The system must be scalable to handle high read Queries Per Second (QPS) and accommodate periodic write spikes (e.g., during bulk imports or price updates).
- Caching: Implement a comprehensive caching strategy, including object caching, edge caching, and search engine caching, along with robust invalidation mechanisms.
- Consistency: Ensure consistency across the relational database, caches, and search index. Specifically, implement "read-your-writes" consistency for administrative users.
Deliverables
- Define high-level API endpoints for CRUD, search, and bulk import operations, including example request and response structures.
- Propose a relational database schema, explicitly demonstrating the self-join for category hierarchies.
- Discuss strategies for achieving scalability, managing caching, and ensuring consistency.