Database Design Mental Models
A durable set of data modeling questions for relational and document databases.
- Status
- evergreen
- Visibility
- public
- Category
- Databases
- Difficulty
- intermediate
- Published
- Jun 28, 2026
- Updated
- Jun 28, 2026
The Core Question
Data modeling starts with access patterns, consistency needs, and change frequency, not with a favorite database engine.
Ask First
- What are the top read paths?
- What are the top write paths?
- Which operations must be transactional?
- Which fields change frequently?
- Which entities grow without bound?
- What must be queryable by support, analytics, or operations?
- What data must be deleted or anonymized?
Relational Bias
Use a relational model when relationships, constraints, joins, reporting, and transactions are central. Postgres is a strong default for many backend systems because it can stay simple while the product changes.
Document Bias
Use a document model when the aggregate shape is natural, nested data is read together, and schema flexibility is more valuable than cross-document joins.
Design Smells
- A table or collection called
data. - JSON fields used to avoid understanding the domain.
- Missing indexes on primary query paths.
- No migration strategy.
- No ownership of retention or deletion.
- Queries that only work because the dataset is still tiny.
Source Links
Related Notes
Database Design Checklist
A checklist for choosing and shaping relational or document data models.
MongoDB Data Modeling Notes
A document-database mental model for aggregates, embedding, references, indexes, and operational tradeoffs.
PostgreSQL Production Notes
Operational Postgres concepts for backend engineers: schemas, indexes, transactions, migrations, and reliability.
MongoDB Data Modeling Checklist
A checklist for deciding when to embed, reference, index, and evolve MongoDB documents.
PostgreSQL Production Checklist
A compact checklist for Postgres-backed backend services.
Backlinks
Database Design Checklist
A checklist for choosing and shaping relational or document data models.
Backend and AI Infrastructure Roadmap
A role-readiness roadmap for backend, cloud, data, AI API, and production infrastructure skills.
MongoDB Data Modeling Notes
A document-database mental model for aggregates, embedding, references, indexes, and operational tradeoffs.
PostgreSQL Production Notes
Operational Postgres concepts for backend engineers: schemas, indexes, transactions, migrations, and reliability.