Lean storage

As explained in The Art of Code

Lean storage is a software pattern that minimizes unnecessary retained data and storage consumption.

Lean storage minimizes unnecessary retained data, storage consumption, and accumulated operational waste. Keeping less data reduces hardware needs, energy use, and ongoing system pressure. section 8.4.3 section 8.6

Customer table review

Review a PostgreSQL customer table that stores names, addresses, and one of two profile types. Inspect data types, field sizes, and redundant information, then improve and normalize the design. The practical question is not only what can be removed, but what should never be stored unnecessarily. section 8.4.3

Apply deletion and retention decisions carefully: privacy laws may grant deletion rights, while finance, healthcare, employment, or other legal duties may require data to remain for a minimum period. section 8.4.3

Review storage for oversized fields, redundant records, inefficient queries, unbounded caches, and unnecessarily large datasets. Prefer the smallest safe improvement when cleanup could harm clarity or compliance. section 8.5.2

Inspect the customer-table exercise while comparing field sizes, data types, redundancy, and normalization choices. section 8.4.3

How The Art of Code covers it

How deep it goes

Explains storage review through a PostgreSQL exercise and practical waste signals, but stops short of prescribing a universal schema.

Examples

Uses a PostgreSQL customer-table exercise involving field sizes, data types, profile types, redundancy, and normalization.

What it assumes

Assumes familiarity with PostgreSQL tables and recognizes that legal retention duties can constrain deletion decisions.

What you can do after

Apply lean storage via PostgreSQL by reviewing schema sizes, removing redundancy, normalizing data, and checking retention constraints.

How it connects

Connects data retention, normalization, privacy law, sustainability, and green design patterns.

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Related concepts

• normalizationuses · Normalization is the process of transforming a value, representation, or data structure to satisfy a specified standard, scale, or structural constraint.
• retention policyuses · A retention policy is a rule specifying what data or records are preserved, for how long, and under what conditions they may be archived, deleted, or otherwise disposed of.

This explainer was generated by Manning's knowledge graph from the text of The Art of Code. The section links point to the parts of the book it draws on.