# 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 pro…

- **Type:** Skill
- **Install:** `agentstack add skill-azure-documentdb-agent-kit-data-modeling`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Azure](https://agentstack.voostack.com/s/azure)
- **Installs:** 0
- **Category:** [Databases](https://agentstack.voostack.com/c/databases)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Azure](https://github.com/Azure)
- **Source:** https://github.com/Azure/documentdb-agent-kit/tree/main/skills/data-modeling

## Install

```sh
agentstack add skill-azure-documentdb-agent-kit-data-modeling
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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.

## Decision framework

| Relationship | Cardinality | Access pattern | Recommendation |
|---|---|---|---|
| One-to-One | 1:1 | Always together | Embed |
| One-to-Few | 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.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Azure](https://github.com/Azure)
- **Source:** [Azure/documentdb-agent-kit](https://github.com/Azure/documentdb-agent-kit)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-azure-documentdb-agent-kit-data-modeling
- Seller: https://agentstack.voostack.com/s/azure
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.