System Design Cheat Sheet Hot! 〈SIMPLE | 2026〉

Start with relational. Scale with read replicas → cache → sharding → NoSQL when needed. 4. Caching Strategies | Strategy | How it works | Best for | |----------|-------------|-----------| | Cache-aside | App checks cache → misses DB → writes cache | Read-heavy workloads | | Read-through | Cache sits in front of DB | Consistent data, complex queries | | Write-through | Write to cache + DB synchronously | Write-heavy, need consistency | | Write-behind | Write to cache → async write to DB | High write throughput, eventual consistency | | Refresh-ahead | Cache auto-refreshes near-expiry data | Predictable access patterns |

Stale data, thundering herd, cache stampede. 5. Asynchronous Processing Patterns | Pattern | Description | Use case | |---------|-------------|----------| | Message queue | Producer → queue → consumer | Task distribution, load smoothing | | Pub/Sub | One-to-many fanout | Event-driven updates, notifications | | Event sourcing | Store state as event log | Audit, replay, CQRS | | CQRS | Separate read/write models | Complex domains, high read/write asymmetry | | Saga | Distributed transaction via compensating events | Cross-service consistency | system design cheat sheet

Pick 2 of (C, A, P) — in practice, AP (eventual consistency) or CP (strong consistency with possible downtime). 3. Database Selection Guide | Workload | Recommendation | Rationale | |----------|---------------|-----------| | Strong ACID, complex joins | PostgreSQL, MySQL (RDBMS) | Transactions, referential integrity | | High write throughput, simple lookups | Cassandra, DynamoDB | Partitioned wide-column | | Flexible schema, rapid iteration | MongoDB, Couchbase | Document store | | Search | Elasticsearch | Inverted indexes, full-text | | Real-time analytics | ClickHouse, Druid | Columnar storage | | Graph relationships | Neo4j, ArangoDB | Graph traversal | Start with relational