Skip to main content

documentdb-data-modeling

Data modeling patterns for Azure DocumentDB — embed vs reference, 16 MB document limit, denormalization for read-heavy workloads, schema versioning. Use when designing new schemas, reviewing existing data models, migrating from SQL, deciding between embedding and referencing, modeling one-to-one / one-to-many / many-to-many relationships, or troubleshooting document-size and query-performance problems that stem from the data model.

Quellinformationen

Repository
Azure/documentdb-agent-kit
Letzte Quellaktivität
31. Juli 2026 um 22:12
Erkannte Sprache von SKILL.md
Englisch
Sterne
6
Forks
11

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

Datei-Explorer
6 Dateien

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
documentdb-data-modeling
description
Data modeling patterns for Azure DocumentDB — embed vs reference, 16 MB document limit, denormalization for read-heavy workloads, schema versioning. Use when designing new schemas, reviewing existing data models, migrating from SQL, deciding between embedding and referencing, modeling one-to-one / one-to-many / many-to-many relationships, or troubleshooting document-size and query-performance problems that stem from the data model.
license
MIT
# Data Modeling — Azure DocumentDB Guiding principle: **"Data that is accessed together should be stored together."** Each rule follows the same shape — why it matters → incorrect example → correct example → references. ## Rules - [model-embed-vs-reference](model-embed-vs-reference.md) — Embed data accessed together; reference unbounded N-sides. - [model-16mb-limit](model-16mb-limit.md) — Stay well under the 16 MB BSON document limit; plan for steady-state growth. - [model-denormalize-reads](model-denormalize-reads.md) — Denormalize for read-heavy workloads; pre-compute aggregates to avoid `$lookup`. - [model-schema-versioning](model-schema-versioning.md) — Add a `schemaVersion` field and migrate documents lazily. - [model-large-field-split](model-large-field-split.md) — Split a large, low-compressibility field into a side collection keyed by `_id` to avoid the PostgreSQL TOAST detoast tax on scans. Companion tool: [`scripts/toast-split-advisor.sh`](../../scripts/toast-split-advisor.sh). ## Companion tool (analysis only) [`scripts/toast-split-advisor.sh`](../../scripts/toast-split-advisor.sh) measures heap vs TOAST bytes on a live local container and reports **where** a large field should be split out — it never moves data: ```bash bash scripts/toast-split-advisor.sh --db <name> [--json] ``` ## Decision framework | Relationship | Cardinality | Access pattern | Recommendation | |---|---|---|---| | One-to-One | 1:1 | Always together | Embed | | One-to-Few | 1:N (N < ~100) | Usually together | Embed array | | One-to-Many | 1:N (N > ~100) | Often separate | Reference | | Many-to-Many | M:N | Varies | Two-way reference or junction collection | See each rule file for the full reasoning and code examples.
Auf GitHub ansehen