# Document model

Learn how to think in a document model, how SurrealDB maps tables and records to documents, and where to find guides on nested data, schema modes, and common patterns including SurrealQL and MongoDB-style mappings.

One of the most popular database models is that of a document database. It provides a flexible way to store data, allowing for nested structures and relationships to be stored within a single document.

In a document database, data is stored in the form of documents (which usually resemble JSON objects) rather than in rows and columns.

This model offers a level of simplicity and flexibility that can be especially appealing when your data does not naturally fit into a strict tabular format or when the structure of your data frequently changes.

Over the last decade, we have seen a surge of NoSQL databases such as [MongoDB](https://www.mongodb.com/), [CouchDB](https://couchdb.apache.org/), and [DynamoDB](https://aws.amazon.com/dynamodb/), all of which are in the broad category of document stores (although with varying specific features).

But how do you “think” in a document model database? Thinking in a document model means orienting your data design around the entities as you naturally represent them in your applications, rather than forcing your data into normalised or heavily structured relational schemas.

## Core concepts of document-oriented modelling

In a document-oriented system you typically work with:

- **Self-describing records**: Data is grouped into records that carry their own structure (fields, nested objects, arrays), often similar to JSON in application code.
- **Embedding vs linking**: Related data can live inside the same document (embedding) or be referenced with [record links](/docs/reference/query-language/language-primitives/record-links.md) or graph-style relations when you need shared entities or strict edges.
- **Flexible schema**: Tables can mix different shapes when you choose a schemaless workflow, or you can tighten definitions with [`DEFINE TABLE`](/docs/reference/query-language/statements/define/table.md) and field types when you need validation and tooling support.

## Where to go next

The guides in this section break these ideas down in more detail:

- [Nested objects and arrays](/docs/learn/data-models/document/nested-objects-and-arrays.md): worked examples with nested structures, record IDs, and linking documents.
- [Schema modes](/docs/learn/data-models/document/schema-modes.md): creating and retrieving documents, and how schemaless usage compares to defining a schema.
- [Common patterns](/docs/learn/data-models/document/common-patterns.md): concept mapping to other document stores, benefits, MongoDB-style SurrealQL examples, and further resources.

For statement-level reference and CRUD details, see the [`CREATE`](/docs/reference/query-language/statements/create.md), [`SELECT`](/docs/reference/query-language/statements/select.md), [`UPDATE`](/docs/reference/query-language/statements/update.md), and [`DELETE`](/docs/reference/query-language/statements/delete.md) statements, and the [SurrealQL documentation](/docs/reference/query-language.md).