# Designing Data-Intensive Applications vs The Pragmatic Programmer

Status: reviewed
Research basis: mini-only

Verdict: ✅ Complementary

Conflict: 10%
Overlap: 35%
Complementarity: 80%

## Loading Decision

Use together when the task changes state, events, schemas, queues, projections, caches, consistency, or ownership while also needing The Pragmatic Programmer pressure.

## Book A Pressure

- Designing Data-Intensive Applications should drive tasks where source of truth, consistency, durability, replay, schemas, replication, partitioning, or distributed failure dominate.
- Evidence: `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 3-5: applies where correctness depends on data ownership, consistency, durability, replication, partitioning, schema evolution, event flow, replay, or derived data.

## Book B Pressure

- The Pragmatic Programmer should drive tasks where ownership, DRY knowledge, orthogonality, reversibility, tracer feedback, automation, and contracts dominate.
- Evidence: `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 3-5: applies as a general engineering operating style for accountable delivery, adaptability, fast feedback, and easy-to-change code.

## Complementary Forces

- Claim: Designing Data-Intensive Applications contributes source-of-truth, consistency, replay, schema-evolution, partitioning, and distributed-failure pressure; The Pragmatic Programmer contributes ownership, DRY-knowledge, orthogonality, reversibility, tracer-feedback, automation, and contract pressure. Together they are useful only where both scopes are active.
- Evidence:
  - `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 13-30: requires explicit source of truth, failure semantics, workload facts, data ownership, storage/index choices, derived-data lag and repair, write visibility, idempotent retry/replay, ordering scope, evolving schemas, replication/partitioning/transactions, fault models, coordination costs, recoverable batch/stream processing, and service boundaries by data ownership.
  - `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 39-53: fires on duplicated facts, shotgun edits, hard-coded volatile details, high uncertainty, prototype/tool output becoming truth, growing prose specs, hidden assumptions, boundary errors/resources, shared state/async/locks, repeated manual steps, bad tests, unexplained behavior, and local decay.

## Overlap

- Claim: They overlap where both affect boundaries, explicit responsibilities, tests, coupling reduction, and avoiding hidden assumptions; the overlap score reflects how often an agent would receive similar pressure from both.
- Evidence:
  - `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 46-55: checks source of truth, consistency/durability/staleness/conflicts, retry/replay/reordering, safe evolution, workload-matched storage, invariant-protecting isolation, rebuildable streams/projections, ownership-aligned services, observability, and no exactly-once wishful thinking.
  - `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 56-65: checks authoritative knowledge, independent concerns and reversible choices, feedback, accepted prototype/tool behavior, contracts/failures/resources, visible state/coupling, automation, relevant tests, communicative artifacts, and touched-area improvement/containment.

## Conflicts

- Claim: The tension is over-modeling: the non-data rule set may improve structure, but DDIA requires explicit data semantics before abstractions hide source-of-truth or failure behavior.
- Evidence:
  - `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 7-9: corrects local-happy-path thinking about writes, reads, queues, caches, replicas, clocks, and downstream side effects.
  - `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 39-53: fires on duplicated facts, shotgun edits, hard-coded volatile details, high uncertainty, prototype/tool output becoming truth, growing prose specs, hidden assumptions, boundary errors/resources, shared state/async/locks, repeated manual steps, bad tests, unexplained behavior, and local decay.

## Use Together When

- Use together when the other design concern changes source of truth, consistency, schema evolution, event flow, replay, derived data, partitions, or ownership boundaries.

## Prefer One When

- Prefer DDIA when consistency, schemas, replay, ordering, source of truth, or distributed data failure is the hard part; prefer the other book when those data semantics are not in scope.

## Source Basis

- `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 3-5: applies where correctness depends on data ownership, consistency, durability, replication, partitioning, schema evolution, event flow, replay, or derived data.
- `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 7-9: corrects local-happy-path thinking about writes, reads, queues, caches, replicas, clocks, and downstream side effects.
- `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 13-30: requires explicit source of truth, failure semantics, workload facts, data ownership, storage/index choices, derived-data lag and repair, write visibility, idempotent retry/replay, ordering scope, evolving schemas, replication/partitioning/transactions, fault models, coordination costs, recoverable batch/stream processing, and service boundaries by data ownership.
- `designing-data-intensive-applications/designing-data-intensive-applications.mini.md` lines 46-55: checks source of truth, consistency/durability/staleness/conflicts, retry/replay/reordering, safe evolution, workload-matched storage, invariant-protecting isolation, rebuildable streams/projections, ownership-aligned services, observability, and no exactly-once wishful thinking.
- `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 3-5: applies as a general engineering operating style for accountable delivery, adaptability, fast feedback, and easy-to-change code.
- `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 7-9: corrects local-edit and ritual optimization by owning outcomes, reducing duplicated knowledge, keeping concerns independent, proving assumptions early, automating repeated work, and making intent clear.
- `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 39-53: fires on duplicated facts, shotgun edits, hard-coded volatile details, high uncertainty, prototype/tool output becoming truth, growing prose specs, hidden assumptions, boundary errors/resources, shared state/async/locks, repeated manual steps, bad tests, unexplained behavior, and local decay.
- `the-pragmatic-programmer/the-pragmatic-programmer.mini.md` lines 56-65: checks authoritative knowledge, independent concerns and reversible choices, feedback, accepted prototype/tool behavior, contracts/failures/resources, visible state/coupling, automation, relevant tests, communicative artifacts, and touched-area improvement/containment.

## Review Notes

- External context was not used as decisive evidence for Designing Data-Intensive Applications vs The Pragmatic Programmer; the verdict is based on the cited local `mini` line ranges.
