Data Modeling
Schemas, keys, normalization and sharding for real workloads.
7 notes · 24 min total
- 1Entities, Keys and RelationshipsTurn core entities into tables with primary and foreign keys, model 1:N and N:M relationships, and keep data correct at scale.6 min
- 2Database Model OptionsRelational, document, key-value, wide-column and graph databases: how each models data and when to choose it.7 min
- 3Schema Design FundamentalsHow data volume, access patterns and consistency needs shape your tables, keys and database choice.3 min
- 4Normalization vs DenormalizationWhy you store each fact once by default, and the few cases where duplicating data for faster reads is worth it.2 min
- 5IndexingHow to choose indexes that match your most important queries, and how to tie them to your API endpoints.1 min
- 6ShardingHow to split data across databases with a shard key that keeps related data together and avoids cross-shard queries.2 min
- 7Data Modeling in an InterviewA step-by-step checklist for sketching a schema during a system design interview, plus sensible database defaults.3 min