System Design Tradeoffs Guide - Master Index

A comprehensive reference for understanding key tradeoffs in system design interviews. This guide explains when to use each approach, why, and what you gain or sacrifice.

Complete Topic List

This master guide has been divided into focused topic files for easier reference. Each file contains:

Detailed comparison tables
Deep dives with examples
Real-world tradeoff analysis
Interview questions with answers

1. Database Tradeoffs

SQL vs NoSQL, common databases, geospatial queries (PostgreSQL + PostGIS, Redis Geo, MongoDB, Elasticsearch, DynamoDB, S2/H3 geometry), read replicas vs sharding, normalization vs denormalization, data structures & indexing

Key topics:

When to use SQL vs NoSQL
Location query patterns (Uber, food delivery, GIS)
Scaling strategies (read replicas, sharding, geo-partitioning)

2. Caching Strategies

Cache Aside, Write-Through, Write-Behind, Refresh-Ahead patterns with deep dives, TTL strategies, cache invalidation, cache stampede solutions

Key topics:

Cache pattern selection
TTL tuning for different use cases
Preventing cascading failures

3. API Design

REST vs gRPC vs GraphQL vs WebSockets vs SSE vs WebHooks with comprehensive comparison table, detailed pros/cons, when to use each, real-time patterns

Key topics:

API pattern selection matrix
Real-time communication (WebSockets vs SSE)
Mobile vs server API design

4. Storage Tradeoffs

Object Storage (S3) vs Block Storage (EBS) vs File Storage (EFS/NFS), decision matrix, cost analysis, Instagram/Dropbox design examples

Key topics:

Storage type selection
Cost optimization strategies
Cloud storage architecture

5. Communication Patterns

Synchronous vs Asynchronous, polling patterns (short/long polling, WebSockets, SSE), message queues (Pub/Sub vs Queue), chaos engineering, retry mechanisms with exponential backoff

Key topics:

Service communication patterns
Message queue strategies
Failure handling and resilience

6. Scalability & Reliability

Vertical vs Horizontal scaling, CAP theorem, load balancing strategies, replication patterns, circuit breaker pattern, multi-region failover, disaster recovery

Key topics:

Scaling decision making
High availability patterns
Fault tolerance strategies

7. Data Processing

Batch vs Stream processing, Lambda vs Kappa architecture, tools comparison (Spark, Flink, Kafka Streams, Kinesis), real-time analytics, data warehouse design for scale

Key topics:

Batch vs stream tradeoffs
Real-time analytics at scale
Fraud detection and recommendation systems

8. Architecture Patterns

Monolith vs Microservices, architecture evolution, when to migrate, data consistency across services, saga pattern, service design principles

Key topics:

Monolith vs microservices decision
Distributed transaction patterns
Service boundary design

9. REST & gRPC Best Practices

REST API design principles, HTTP methods semantics, versioning strategies, pagination strategies (offset, cursor, page, seek), filtering & sorting, caching optimization, gRPC proto design, streaming strategies, performance tuning

Key topics:

Resource-oriented REST design
Pagination for large datasets (100M+ records)
gRPC for microservices (10K+ QPS)
API optimization techniques (compression, rate limiting, async)
Field selection and sparse fieldsets

10. Kafka Deep Dive

Apache Kafka from ground up, core components (brokers, topics, partitions, replicas, consumer groups), producers and consumers, replication and high availability, Zookeeper vs KRaft, performance tuning, monitoring, exactly-once semantics, real-world patterns

Key topics:

Kafka architecture and components
Producer batching, acknowledgments, idempotence
Consumer offset management, rebalancing, lag monitoring
High availability with replication (99.99% uptime)
Exactly-once payment processing
Event sourcing and CQRS patterns

11. Design Patterns

CQRS, Event Sourcing, Saga Pattern, Circuit Breaker, Bulkhead, Retry with exponential backoff, Eventual Consistency, Sharding, Cache-Aside, Write-Through, Multi-Tenancy, API Gateway, Strangler Fig

Key topics:

CQRS for read/write optimization
Event Sourcing for audit trails and time-travel
Saga pattern for distributed transactions
Fault tolerance patterns (circuit breaker, bulkhead, retry)
Sharding strategies for scalability
Migration patterns (strangler fig)
Multi-tenancy isolation levels

Redis

Zookeeper