Azure Cosmos DB

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---
name: cosmosdb-best-practices
description: "Azure Cosmos DB performance optimization and best practices for NoSQL data modeling, partitioning, queries, indexing, throughput, vector search, full-text search, global distribution, and SDK usage. Use when writing, reviewing, or refactoring applications that interact with Azure Cosmos DB for NoSQL. Do not use for relational databases, Redis, Elasticsearch, DynamoDB, Cassandra, Azure DocumentDB, or Cosmos DB APIs for PostgreSQL or MongoDB."
---

# Azure Cosmos DB Best Practices

Comprehensive performance optimization guide for Azure Cosmos DB applications, containing 100+ rules across 12 categories, prioritized by impact to guide automated refactoring and code generation.

## When to Apply

Reference these guidelines when:
- Designing data models for Cosmos DB
- Choosing partition keys
- Writing or optimizing queries
- Implementing SDK patterns
- Using the Cosmos DB Emulator for local development
- Inspecting or managing Cosmos DB data with developer tooling
- Implementing vector search or RAG features on Cosmos DB
- Reviewing code for performance issues
- Configuring throughput and scaling
- Building globally distributed applications

## Rule Categories by Priority

| Priority | Category | Impact | Prefix |
|----------|----------|--------|--------|
| 1 | Data Modeling | CRITICAL | `model-` |
| 2 | Partition Key Design | CRITICAL | `partition-` |
| 3 | Query Optimization | HIGH | `query-` |
| 4 | SDK Best Practices | HIGH | `sdk-` |
| 5 | Indexing Strategies | MEDIUM-HIGH | `index-` |
| 6 | Throughput & Scaling | MEDIUM | `throughput-` |
| 7 | Global Distribution | MEDIUM | `global-` |
| 8 | Monitoring & Diagnostics | LOW-MEDIUM | `monitoring-` |
| 9 | Design Patterns | HIGH | `pattern-` |
| 10 | Developer Tooling | MEDIUM | `tooling-` |
| 11 | Vector Search | HIGH | `vector-` |

## Quick Reference

### 1. Data Modeling (CRITICAL)

- [model-embed-related](rules/model-embed-related.md) - Embed related data retrieved together
- [model-reference-large](rules/model-reference-large.md) - Reference data when items get too large
- [model-avoid-2mb-limit](rules/model-avoid-2mb-limit.md) - Keep items well under 2MB limit
- [model-id-constraints](rules/model-id-constraints.md) - Follow ID value length and character constraints
- [model-nesting-depth](rules/model-nesting-depth.md) - Stay within 128-level nesting depth limit
- [model-numeric-precision](rules/model-numeric-precision.md) - Understand IEEE 754 numeric precision limits
- [model-denormalize-reads](rules/model-denormalize-reads.md) - Denormalize for read-heavy workloads including pre-computed aggregates
- [model-schema-versioning](rules/model-schema-versioning.md) - Version your document schemas
- [model-type-discriminator](rules/model-type-discriminator.md) - Use type discriminators for polymorphic data
- [model-json-serialization](rules/model-json-serialization.md) - Handle JSON serialization correctly for Cosmos DB documents
- [model-relationship-references](rules/model-relationship-references.md) - Use ID references with transient hydration for document relationships

### 2. Partition Key Design (CRITICAL)

- [partition-high-cardinality](rules/partition-high-cardinality.md) - Choose high-cardinality partition keys
- [partition-avoid-hotspots](rules/partition-avoid-hotspots.md) - Distribute writes evenly
- [partition-hierarchical](rules/partition-hierarchical.md) - Use hierarchical partition keys for flexibility; order levels broad→narrow
- [partition-query-patterns](rules/partition-query-patterns.md) - Align partition key with query patterns
- [partition-synthetic-keys](rules/partition-synthetic-keys.md) - Create synthetic keys when needed
- [partition-key-length](rules/partition-key-length.md) - Respect partition key value length limits
- [partition-immutable-key](rules/partition-immutable-key.md) - Choose immutable properties as partition keys
- [partition-20gb

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